JP4218874B2 - Evaluation method of data string composed of characters, etc., program for executing the evaluation method, and execution result of the evaluation method - Google Patents

Description

【００６２】
そして、比較データ列の中のデータの組の全てについて距離情報が一致するとき（つまり、上記の表で評価点数が１のとき）に、当該比較データ列の中に所定のモチーフが存在すると判断する。上記の表の例では、比較データ列１の中にはモチーフは存在しないが、比較データ列２の中にはモチーフが存在すると判断することができる。
【００６３】
本発明の好適な実施形態について説明したが、本発明は上記の実施形態に限定されるものではない。
例えば、上記の説明では、説明の便宜のため、基準データ列及び比較データ列の類似性評価方法として説明したが、類似性を評価する為の２文字からなる配列データ（例：Ｃ＿＿Ｔ）に配列内の位置情報（＝ｉ）を付加し、且つ‘Ｃ’⇔‘Ｔ’間の距離を数値化（＝ｗ）して１件のミニマムなコア配列データを、「ｉＣｗＴ」、例えば「１Ｃ２Ｔ」のように表現して記憶させることにより、
▲１▼基準データ列及び比較データ列が共有する連続文字配列データを出力する事 が可能になる。
▲２▼ 又、▲１▼と同様に、基準データ列及び比較配列データのそれぞれが持つ固有の連続文字配列を出力する事が出来る。
▲３▼ 遺伝子解析上重要な課題である１塩基置換配列（ＳＮＰ）を確実に把握することが出来る。
【００６４】
その他、ＤＮＡ配列分析の為の、客観的で信頼性の高い効率的な解析手法の基礎とする事が出来る。
また、本発明では、上記で説明した処理を実行するプログラムを光ディスクや磁気ディスク等の記録媒体に格納し、この記録媒体から読み出した前記プログラムをコンピュータに読み込んで実行させることが可能である。
さらに、本発明では、第一の実施形態〜第九の実施形態を適宜に組み合わせて実施することが可能である。例えば、第六の実施形態にしたがって複数のデータ列の中から共通部分を抜き出した後に、第一の実施形態にしたがって、当該共通部分からなるデータ列について、データの並び順の一致性を判断するようにすることも可能である。
また、本発明は、上記のような一次元的なデータ列に限らず、二次元的なデータ列にも適用が可能で、比較画像の類似性を判断するパターン解析にも適用が可能である。
【００６５】
【発明の効果】
このように、本発明によれば、簡単な方法でデータ列の類似性及び共通性を客観的に評価できるものである。さらに、データの数が多くなっても、二つのデータからなる組を抽出するだけであり、過度に複雑な処理プロセスを必要とせずコンピュータの処理能力に大きな負担をかけることなく客観的な評価を安価かつ短時間で行うことが出来る。従って、パーソナルコンピュータ程度の汎用コンピュータによる処理でもある程度の規模の文字列間の評価を行うことができ、又、処理を分散し複数のコンピュータで並行的な処理を行う事も可能になる。
【図面の簡単な説明】
【図１】本発明の評価方法を説明するフローチャートである。
【図２】本発明の評価方法を実行する装置の構成を示すブロック図である。
【図３】本発明の評価方法の第一の実施形態にかかる具体例で、ｋ＝１の比較データ列「Ａ，Ｂ，Ｃ，Ｄ，Ｅ」の評価結果を示すものである。
【図４】本発明の評価方法の第一の実施形態にかかる具体例で、ｋ＝２の比較データ列「Ａ，Ｃ，Ｂ，Ｄ，Ｅ」の評価結果を示すものである。
【図５】本発明の評価方法の第一の実施形態にかかる具体例で、ｋ＝３の比較データ列「Ｃ，Ｂ，Ａ，Ｅ，Ｄ」の評価結果を示すものである。
【図６】本発明の評価方法の第一の実施形態にかかる具体例で、ｋ＝４の比較データ列「Ｅ，Ａ，Ｂ，Ｄ，Ｃ」の評価結果を示すものである。
【図７】本発明の評価方法の第一の実施形態にかかる具体例で、ｋ＝５の比較データ列「Ｅ，Ｄ，Ｃ，Ｂ，Ａ」の評価結果を示すものである。
【図８】第二の実施形態の類似性評価の結果を示す表である。
【図９】第三の実施形態の類似性評価の結果を示す表である。
【図１０】第四の実施形態の類似性評価の結果を示す表である。
【図１１】第五の実施形態の類似性評価の結果を示す表である。
【図１２】本発明の評価方法の第五の実施形態にかかる具体例で、ｋ＝１の比較データ列「Ｃ、Ｔ、Ｃ、Ｇ、Ａ」の評価結果を示すものである。
【図１３】本発明の評価方法の第五の実施形態にかかる具体例で、ｋ＝２の比較データ列「Ｃ，Ｔ，Ｔ，Ｇ，Ａ」の評価結果を示すものである。
【図１４】本発明の評価方法の第五の実施形態にかかる具体例で、ｋ＝３の比較データ列「Ｔ，Ｃ，Ｇ，Ａ，Ｃ」の評価結果を示すものである。
【図１５】本発明の評価方法の第五の実施形態にかかる具体例で、ｋ＝４の比較データ列「Ａ，Ｇ，Ｃ，Ｔ，Ｃ」の評価結果を示すものである。
【図１６】本発明の評価方法の第五の実施形態にかかる具体例で、ｋ＝５の比較データ列「Ａ，Ｇ，Ｔ，Ａ，Ｃ」の評価結果を示すものである。
【図１７】第六の実施形態のデータ列が共有する配列部分を検出する処理の結果を示す表である。
【図１８】第六の実施形態の処理の手順を説明するためのフローチャートである。
【図１９】第七の実施形態のデータ列が共有する配列を元の配列として復元する処理の結果を示す表である。
【図２０】第七及び第八の実施形態の処理の手順を説明するためのフローチャートである。
【符号の説明】
１ 評価装置
１１ 入力部
１３ 比較・演算部
１４ 記憶部
１４ａ 第一の記憶領域
１４ｂ 第二の記憶領域
１４ｃ 第三の記憶領域
１５ 表示部[0001]
BACKGROUND OF THE INVENTION
The present invention objectively determines how similar these data strings are, and how common they are among a plurality of data strings consisting of a plurality of numerical values, symbols, characters, figures, or combinations thereof. Evaluation of data strings consisting of characters etc.apparatusas well asComputer program for data string evaluation apparatusAbout.
[0002]
[Prior art]
Conventionally, various methods have been proposed as methods for determining the similarity of data strings composed of data such as characters and numbers (see, for example, Patent Document 1 and Patent Document 2).
[0003]
[Patent Document 1]
JP-A-6-139224
[Patent Document 2]
JP 20002-202983 A
[0004]
However, even when the conventional method as described above is used, when there are a plurality of comparison data strings to be compared with respect to one reference data string, the plurality of comparison data strings are compared with the reference data string. It may be difficult to rank how close they are.
[0005]
For example, with respect to a reference data string consisting of five characters “A, B, C, D, E”, three comparison data strings “A, C, B, D, E”, “C, B, A, E” are used. , D "and" E, A, B, D, C "," A, C, B, D, E "is closest to the reference data string" A, B, C, D, E " Although it can be easily judged, it is not possible to objectively evaluate which of “C, B, A, E, D” and “E, A, B, D, C” is closer to the reference data string. It was difficult.
Furthermore, as the number of data such as characters constituting the reference data string and comparison data string increases, the information that must be processed increases significantly. For example, in order to analyze a long character sequence such as a DNA base sequence consisting of four types of AGTC data and 20 types of amino acid sequences constituting a protein, it cannot be processed without using an ultra-high-speed super-large computer. is the current situation.
[0006]
As a method or program for analyzing the base sequence or amino acid sequence of DNA as described above, a technique related to a system for searching and extracting a specific motif sequence (see Patent Document 3), or a method related to SNP (single nucleotide polymorphism) detection ( Various types have been proposed, such as Patent Document 4).
[0007]
[Patent Document 3]
JP 2000-060553 A
[Patent Document 4]
JP 2002-063175 A
[0008]
However, even with the methods, programs, and systems described in Patent Document 3 and Patent Document 4, there is a problem that analysis requires a lot of time and labor. Moreover, it is extremely difficult to find a common part from long character code sequences such as DNA base sequences and amino acid sequences. For example, how common is the amino acid sequence of human amino acid sequences consisting of thousands of letters, etc., and monkeys, worms, mice and other animals that are comparative controls, and what parts are common? The current situation is that researchers are visually observing the arrangement of characters and the like to be compared, and the task of searching for a common portion for a plurality of comparison targets is problematic in that it requires enormous time and effort.
[0009]
[Problems to be solved by the invention]
The present invention has been made in view of the above-mentioned problems. It is possible to objectively evaluate the similarity of data strings by a simple method. Even if the number of data such as characters increases, the processing power of the computer is improved. Evaluation of data strings consisting of characters that do not place an excessive burdenapparatusas well asComputer program for data string evaluation apparatusA data string evaluation device composed of characters or the like that can easily search for a common part of a plurality of data strings, andComputer program for data string evaluation apparatusThe purpose is to provide.
[0010]
[Means for Solving the Problems]
In order to achieve the above object, the inventor of the present invention decomposes each data string to be compared into a data set composed of two characters, etc., and the arrangement order of the characters is the same for each set. It was found that similarity (commonality) can be easily determined with a simple program by determining whether or not there is.
  That is, the invention according to claim 1 is an evaluation apparatus for evaluating how similar the comparison data composed of similar data is to a reference data string composed of a plurality of character, numerical value, symbol or graphic data. , A reference data string consisting of a plurality of character, numerical value, symbol or figure data, or a reference data string combining these dataIs received and stored in the storage unitAnd the comparison data stringIs received and stored in the storage unitAn input unit toStored in the storage unitFrom each of the reference data string and the comparison data string, a set of two data is formed without changing the arrangement order.Stored in the storage unit, and stored in the storage unitThe order of the data in the set of comparison data strings;The stored in the storage unitData constituting the set in the reference dataButthe sameA set of dataA comparison unit that compares the order of data; and, as a result of comparison, a first evaluation score is assigned when the arrangement order matches, and a second evaluation score is assigned when the arrangement order does not match, and the comparison Total score obtained by adding the first and second evaluation scores assigned to all pairs extracted from the data stringIn the storage unit, and the total scoreAnd a calculation unit that performs evaluation based on the above.
[0011]
The invention described in claim 2 is configured such that the first evaluation score is 1 point and the second evaluation score is 0 point.
  The similarity evaluation can be determined by how much common parts are included in the data strings to be compared. Then, by defining a certain calculation formula indicating the ratio of the common part in advance and substituting the number of sets that match or the number of sets that do not match, the similarity can be determined. That is, the invention according to claim 3 is an evaluation device for evaluating how similar the comparison data made of similar data is to a reference data string made up of a plurality of character, numerical value, symbol or graphic data. , A reference data string consisting of a plurality of character, numerical value, symbol or figure data, or a reference data string combining these dataIs received and stored in the storage unitAnd the comparison data stringIs received and stored in the storage unitAn input unit toStored in the storage unitA set of two data is formed from the reference data string and the comparison data string.Stored in the storage unit,The stored in the storage unitThe order of the data in the set of comparison data strings;The stored in the storage unitData constituting the set in the reference dataButthe sameA set of dataThe comparison unit for comparing the data arrangement order and the number of sets in which the arrangement order is matched or the number of mismatched sets in the set of the comparison data string is obtained, and the matching set or the mismatch for all the pairs Evaluation of the comparison data string from the ratio of the number of pairsA value is obtained and the evaluation value is stored in the storage unitAnd a calculation unit.
[0012]
  In the present invention, not only similarity but also commonality can be easily determined. That is, the invention according to claim 4 is the data string evaluation device according to any one of claims 1 to 3, wherein the arrangement order is changed from each of the plurality of data strings input from the input unit. Without creating a set of two dataStored in the storage unit, and stored in the storage unitFrom the set, a set in which the order of the data matches in the plurality of data strings is extracted, and the matched set is stored in the storage unit together with position information in the data string for each of the data strings.StoreFor each data string, a set in which the arrangement order and the position information match is stored in the storage unit.StoreIt has a configuration having a calculation unit that reproduces based on the information. In the present invention, as described in claim 5, the present invention can also be applied when the two data are separated. In this case, the distance between the data is added to the arrangement order condition and the comparison is performed.
[0013]
In addition, the present invention can be effectively applied to a huge data string such as a gene base sequence or an amino acid sequence constituting a protein. In the invention according to claim 6, the data constituting the reference data string and the comparison data string is based on four types of character data of A (adenine), G (guanine), T (thymine) and C (cytosine). Is the base sequence of the geneConstitutionIt is as. In the invention according to claim 7, the data constituting the reference data string and the comparison data string are characters or the like relating to 20 kinds of amino acid sequences constituting the protein.ConstitutionIt is as.
[0014]
Of the present inventionComputer program for data string evaluation apparatusCan be provided by being recorded on a magnetic recording medium such as a CD, FD, MO, or DVD, or an optical recording medium. It is also possible to provide via a wireless or wired communication line. Then, the program of the present invention is read into the memory of a personal computer or a dedicated analysis device via a reading device or the like, and the program is executed by the CPU.Device operationIs possible.
[0015]
DETAILED DESCRIPTION OF THE INVENTION
DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described in detail with reference to the drawings.
[First embodiment]
FIG. 1 is a block diagram showing the configuration of an apparatus for executing the evaluation method of the present invention, FIG. 2 is a flowchart of the evaluation method of the present invention, and FIGS. 3 to 7 are specific evaluation examples according to the evaluation method of the present invention. FIG.
First, an evaluation procedure according to the evaluation method of the present invention will be described with reference to FIGS.
[0016]
As shown in FIG. 1, an evaluation apparatus 1 for executing the evaluation method of the present invention includes an input unit 11 such as a keyboard and a mouse, an input from the input unit 11, and a display unit 15 such as a printer and a display. The input / output processing unit 12 that performs the output processing, the storage unit 14 that stores the contents processed by the input / output processing unit 12, and the comparison / computation that performs a predetermined comparison or calculation based on a command from the input / output processing unit 12 And an arithmetic unit 13. As the storage unit 14, a medium such as a RAM, a hard disk, a flexible disk (FD), or a medium such as an optical disk that can read and write predetermined contents according to a command from the input / output processing unit 12 can be used. The storage unit 14 also includes a first storage area 14a for storing a reference data string (reference data string) for performing evaluation and a data string (comparison) to be compared with the reference data string. A second storage area 14b for storing the data string) and a third storage area 14c for storing the evaluation results in terms of scores.
[0017]
As shown in FIG. 2, when performing a predetermined evaluation, first, a reference data string (reference data string) is input from the input unit 11 to the input / output processing unit 12 (step S <b> 1). The input reference data string is stored in the first storage area 14 a in the storage unit 14 by the input / output processing unit 12.
In the following description, the reference data string is assumed to be a data string including five character data “A, B, C, D, and E”.
[0018]
Next, the number n of comparison data strings is input from the input unit 11 to the input / output processing unit 12 (step S2), and the comparison data string is input from the input unit 11 to the input / output processing unit 12 (step S3). The number n of comparison data strings and each comparison data string are stored in the second storage area 14 b in the storage unit 14 by the input / output processing unit 12.
In the following description, comparison data strings to be compared are represented by “A, B, C, D, E” (k = 1), “A, C, B, D, E” (k = 2). , “C, B, A, E, D” (k = 3), “E, A, B, D, C” (k = 4), “E, D, C, B, A” (k = 5) ) (N = 5).
[0019]
Thereafter, the “execution” command is given via the input unit 11 to start the evaluation. Along with the input of “execute”, first, the reference data string stored in the first storage area 14 a is read by the input / output processing unit 12 and sent to the comparison / calculation unit 13. Next, the first comparison data string (k = 1, definition of this number is performed in step S4) stored in the second storage area 14b is read out by the input / output processing unit 12, and the comparison / calculation unit 13 is read out. Sent to.
[0020]
The comparison / calculation unit 13 extracts a set of two data from the comparison data string “A, B, C, D, E” of k = 1 sent from the input / output processing unit 12. At this time, the order of each data “A”, “B”, “C”, “D”, “E” is not changed (step S5).
That is, as shown in FIG. 3, the comparison / calculation unit 13 selects “A, B”, “A, C”... From “A, B, C, D, E”. Ten types of data sets “C, E” and “D, E” are extracted.
It should be noted that 10 types of data sets (sets of two data) corresponding to the 10 types of comparison data sequences are extracted in advance from the reference data sequence (step S16).
[0021]
Then, the data order in the 10 types of sets and the same data set as the data included in each data set are compared with the data order of the reference data string (step S6).
For example, an order (arrangement relationship) between a set of “A, C” extracted from the comparison data string “A, B, C, D, E” and data “A” and data “C” in the reference data string Compare and consider whether they match. In this case, since the order of the data “A” and the data “C” are both “A, C”, it is determined that the order matches (step S7), and the comparison / calculation unit 13 Gives “1” as a score to this set (“A, C” set) (step S8).
[0022]
In this way, evaluation is performed for all 10 types of sets (step S10). When evaluation is completed for all sets, the comparison data string “A, B, C, D, E” of k = 1 is Sum the evaluation scores for all pairs.
Since the comparison data string “A, B, C, D, E” of k = 1 completely matches the reference data string “A, B, C, D, E”, the total evaluation score is As shown in FIG. 3, it becomes a perfect score (10 points). The evaluation score is stored in the third storage area 14c by the input / output processing unit 12 as a comparison data string “A, B, C, D, E” of k = 1.
[0023]
After the evaluation of the comparison data string “A, B, C, D, E” of k = 1, the count of k is incremented by one (steps S12 and S14), and the next comparison data of k = 2 Evaluate column “A, C, B, E, D”.
For the comparison data string “A, C, B, D, E” of k = 2, the order of the data “A”, “C”, “B”, “D”, “E” is not changed. Ten types of data sets are created (step S5).
Then, the comparison is performed in the same procedure as described above (step S6), and it is determined whether or not the order of the data in the reference data sequence matches (step S7).
[0024]
In the comparison data string “A, C, B, D, E” of k = 2, the data “C” and “B” are interchanged with respect to the reference data string. The order of the data of the set is different from the order of the data “B” and “C” in the reference data string. Therefore, as shown in FIG. 4, the comparison / calculation unit 13 assigns “0” as a score to the set of “C, B” (step S <b> 9).
In the comparison data string “A, C, B, D, E” of k = 2, the order of the data of “C”, “B” is relative to the reference data string “A, B, C, D, E”. Since they have only been replaced, the total number of evaluation points is 9 as shown in FIG. This evaluation score is stored in the third storage area 14c by the input / output processing unit 12 as a comparison data string “A, C, B, D, E” of k = 2.
[0025]
The comparison data string of k = 3, k = 4, and k = 5 is similarly evaluated according to the procedure from step S5 to step S10, and the total score is obtained for each comparison data string (step S11). ), And stores the result in the third storage area 14c.
As shown in FIGS. 5 to 7, the comparison data string “C, B, A, E, D” with k = 3 has 6 evaluation points, and the comparison data string “E, A, B, D with k = 4”. , C ”has an evaluation score of 5 points, and the comparison data sequence“ E, D, C, B, A ”of k = 5, which is completely opposite to the data arrangement of the reference data sequence, has 0 points.
[0026]
In this way, after all the five comparison data strings have been evaluated (step S12), the evaluation score is compared with the comparison data string of k = 1 to 5 (step S13).
That is, the comparison / calculation unit 13 reads and compares the evaluation score of the comparison data string of k = 1 to 5 from the third storage area 14c, and ranks the score in descending order.
[0027]
In the comparison data string of k = 1 to 5 described above, the comparison data string “A, B, C, D, E” of k = 1 has the highest evaluation score, and “A, C, B, D, E” ( k = 2), “C, B, A, E, D” (k = 3), “E, A, B, D, C” (k = 4), “E, D, C, B, A” The evaluation score decreases in the order of (k = 5). That is, it represents the similarity (accessibility) of the comparison data string to the reference data string.
[0028]
In the present invention, it is possible to make an objective evaluation that was difficult with the conventional method. For example, the comparison data string “C, B, A, E, D” of k = 3 and the comparison data string “E, A, B, D, C” of k = 4 are conventionally used as the reference data string. Although it was difficult to determine whether they are close, if the similarity is determined from the viewpoint of the distance of the data constituting each comparison data string, the comparison data string of k = 3 is objectively closer to the reference data string It becomes possible to judge.
[0029]
[Second Embodiment]
In the above embodiment, 1 or 0 evaluation points are assigned depending on whether the data is arranged in the same order.
In this embodiment, it is assumed that “similarity” is the ratio of common parts in a data string such as characters to be compared, and the evaluation of similarity is obtained by the following expression.
In the following formula,
(i) Number of data in the reference data string = n, number of data sets in the reference data string = a
Here, the number a of sets is represented by a = n (n−1) / 2.
(ii) Number of data in comparison data string = m, number of data sets in comparison data string = b
Here, the number b of sets is represented by b = m (m−1) / 2.
(iii) Number of common sets of reference data string and comparison data string = c
[0030]
Similarity evaluation value = (c × 2) / (a + b)
[0031]
When the similarity evaluation value is expressed as a percentage (%), the right side of the above formula may be multiplied by 100.
FIG. 8 shows the result of similarity evaluation when the number of data in the reference data string and the comparison data string is the same (both are five, that is, n = m = 5).
As in the first embodiment, the reference data string and the comparison data string (comparison data strings 1, 2, 3) are classified into two data sets. In the example shown in FIG. 8, both the reference data string and the comparison data string can be classified into 10 groups (ie, a = b = 10).
[0032]
Here, as in the first embodiment, it is determined whether or not the data arrangement order in each set matches the data arrangement order of the reference data set.
As shown in FIG. 8, in the comparison data string 1, since there are eight pairs (c = 8) that match the reference data string, each algebra is substituted into the above equation,
Similarity evaluation value = 16/20 (80%).
Similarly, in the comparison data string 2, the similarity evaluation value = 12/20 (60%), and in the comparison data string 3, there is no group having a common arrangement order, and the similarity evaluation value = 0/20 (0%) )
[0033]
[Third embodiment]
The similarity evaluation of the second embodiment can be applied even when the number of data in the reference data string is different from the number of data in the comparison data string. In such a case, the similarity evaluation is also performed. There is an advantage that it can be performed objectively.
In the following third embodiment, it is assumed that the similarity evaluation between the reference data string “ABCDE”, the comparison data string 1 “ACBE”, the comparison data string 2 “BCD”, and the comparison data string 3 “EDC” is performed.
The result of similarity evaluation of the third embodiment is shown in the table of FIG.
In the comparison data string 1, since the number of data m = 4, the number of data sets b = 6, and the number of data sets c = 5 in common with the reference data string, this is substituted into the above equation,
Similarity evaluation value = 10/16 (62.5%). Similarly, for the comparison data 2, the similarity evaluation value = 6/13 (46.2%), and for the comparison data 3, the similarity evaluation value = 0.
[0034]
[Fourth embodiment]
In the first to third embodiments, the similarity is evaluated based only on the arrangement order of the data sets. In the fourth embodiment, the distance between the data of each set is also considered. The similarity is evaluated.
In the example of similarity evaluation illustrated in FIG. 10, three comparison data strings, that is, comparison data string 1 “BBCCA”, comparison data string 2 “CABBC”, and comparison data string 3 “ABCCB” with respect to the reference data string “ABBCC”. Is being evaluated.
[0035]
When a data set is extracted from the reference data string and the comparison data strings 1, 2, and 3, the distance between the data of each group is indicated by a space "_". For example, in the reference data string “ABBCC”, the data set of the first “A” and the fourth “C” is represented by “A__C”.
In each of the comparison data strings 1, 2, and 3, the number of pairs in which the reference data string pair and the arrangement order and distance of the two data coincide with each other is counted, and this is substituted into the above formula to evaluate the similarity. Is going.
[0036]
In the present invention, even in the case of an array in which the number of data constituting the reference data string and the comparison data string increases and the same character / symbol repeatedly occurs, how close the comparison data string is to the reference data string is objective and Since the judgment can be made accurately, the application field is extremely wide. In addition, for example, the character sequence (comparison data string) of DNA of a plurality of organism genes is compared with the character sequence (reference data string) of human DNA, or the amino acid sequence of a protein constituting a cell having a plurality of organisms. It can be applied to the objective and easy judgment of which living organisms are close to humans by comparing amino acid sequences constituting proteins of human cells.
Note that this embodiment can also be applied when the number of reference data strings and comparison data strings are different as shown in FIG.
In the example shown in FIG. 11, the case where the number of data in the comparison data string is larger than the number of data in the reference data string is shown, but similarity evaluation can be performed by the same method as described above.
[0037]
[Fifth embodiment]
Next, a fifth embodiment in which the evaluation method of the present invention is applied to gene sequences will be described with reference to FIGS. 1, 2, and 12 to 16.
[0038]
As shown in FIG. 2, when performing a predetermined evaluation, first, a reference data string (reference data string) is input from the input unit 11 to the input / output processing unit 12 (step S <b> 1). The input reference data string is stored in the first storage area 14 a in the storage unit 14 by the input / output processing unit 12.
In the following description, the reference data string is assumed to be a data string composed of five character data “C, T, C, G, A”.
[0039]
Next, the number n of comparison data strings is input from the input unit 11 to the input / output processing unit 12 (step S2), and the comparison data string is input from the input unit 11 to the input / output processing unit 12 (step S3). The number n of comparison data strings and each comparison data string are stored in the second storage area 14 b in the storage unit 14 by the input / output processing unit 12.
In the following description, comparison data strings to be compared are represented by “C, T, C, G, A” (k = 1), “C, T, T” as shown in FIGS. , G, A ”(k = 2),“ T, C, G, A, C ”(k = 3),“ A, G, C, T, C ”(k = 4),“ A, G, T, A, C ”(k = 5) will be described as five (n = 5).
[0040]
Thereafter, the “execution” command is given via the input unit 11 to start the evaluation. Along with the input of “execute”, first, the reference data string stored in the first storage area 14 a is read by the input / output processing unit 12 and sent to the comparison / calculation unit 13. Next, the first comparison data string (k = 1, definition of this number is performed in step S4) stored in the second storage area 14b is read out by the input / output processing unit 12, and the comparison / calculation unit 13 is read out. Sent to.
[0041]
The comparison / calculation unit 13 extracts two data sets from the comparison data string “C, T, C, G, A” of k = 1 sent from the input / output processing unit 12. At this time, the order of the data “C”, “T”, “C”, “G”, “A” is not changed (step S5), and the distance between the two data is also taken into consideration.
That is, the comparison / calculation unit 13 selects “CT”, “C_C”, “C__G”, “C___A”, “TC” from the comparison data string “C, T, C, G, A” shown in FIG. , “T_G”,... “GA” are extracted. '_' Indicates a blank and indicates the distance between two characters.
[0042]
It should be noted that any character or the like may be inserted in the space, and the number of characters that enter the space between the data, that is, the distance between the data is represented by a numeral, ”,“ C1C ”,“ C2G ”,“ C3A ”,“ T0C ”,“ T1G ”,...,“ G0A ”.
Similar to the previous embodiment, 10 types of data sets (a set of two data) corresponding to the 10 types of sets of the comparison data sequence are extracted in advance from the reference data sequence (steps) S16).
[0043]
Then, with respect to the reference data string and the comparison data string, the arrangement order and distance of the data in the ten kinds of sets are compared (step S6).
For example, the set of “C__G” extracted from the comparison data string “C, T, T, G, A” and the data “C__G” in the reference data string are compared, and the arrangement of both matches, including the distance. Consider whether or not. In this case, it is determined that “C__G” in the comparison data string exists in the reference data array (step S7), and the comparison / calculation unit 13 sets “1” to this group (the group of “C__G”). It is given as a score (step S8).
In addition, instead of assigning the evaluation score “1” or “0”, the number of pairs in which both the arrangement order and the distance match is obtained and substituted into the expressions shown in the second and third embodiments, and similar. Of course, the evaluation of sex may be performed.
[0044]
In this way, evaluation is performed for all 10 types of sets (step S10), and when evaluation is completed for all sets, the comparison data string “C, T,
For “C, G, A”, the scores of all sets of evaluations are summed up.
Since the comparison data string “C, T, C, G, A” with k = 1 completely matches the reference data string “C, T, C, G, A”, the total evaluation score is As shown in FIG. 12, it becomes a perfect score (10 points). This evaluation score is stored in the third storage area 14c by the input / output processing unit 12 as a similarity evaluation value of the comparison data string “C, T, C, G, A” of k = 1.
[0045]
After the evaluation of the comparison data string “C, T, C, G, A” of k = 1, the count of k is increased by one (steps S12 and S14), and the next comparison data of k = 2 Evaluate the column “C, T, T, G, A”.
For the comparison data string “C, T, T, G, A” of k = 2, the order of the data “C”, “T”, “T”, “G”, “A” is not changed. Ten types of data sets are created (step S5).
Then, the comparison is performed in the same procedure as described above (step S6), and it is determined whether or not the order of the data in the reference data sequence matches (step S7).
[0046]
In the comparison data string “C, T, T, G, A” of k = 2, the data “C” and “T” of the third character are replaced with respect to the reference data string. The “TG” set of data created from the columns is not present in the reference data column. Therefore, as shown in FIG. 13, the comparison / calculation unit 13 assigns “0” as a score to the set of “TG” (step S9).
In the comparison data string “C, T, T, G, A” of k = 2, the order of the data of “C”, “T” is relative to the reference data string “C, T, C, G, A”. Although it has only been replaced, the total number of evaluation points is 6 as shown in FIG. The evaluation score is stored in the third storage area 14c by the input / output processing unit 12 as a comparison data string “C, T, T, G, A” of k = 2.
[0047]
The comparison data string of k = 3, k = 4, and k = 5 is similarly evaluated according to the procedure from step S5 to step S10, and the total score is obtained for each comparison data string (step S11). ), And stores the result in the third storage area 14c.
As shown in FIGS. 14 to 16, the comparison data string “T, C, G, A, C” with k = 3 has 6 evaluation points, and the comparison data string “A, G, C, T with k = 4”. , C ”has 3 evaluation points, and k = 5 comparison data string“ A, G, T, A, C ”has 0 evaluation points.
[0048]
In this way, after all the five comparison data strings have been evaluated (step S12), the evaluation score is compared with the comparison data string of k = 1 to 5 (step S13).
That is, the comparison / calculation unit 13 reads and compares the evaluation score of the comparison data string of k = 1 to 5 from the third storage area 14c, and ranks the score in descending order.
[0049]
In the comparison data string of k = 1 to 5 described above, the comparison data string “C, T, C, G, A” of k = 1 has the highest evaluation score, and “C, T, C, G, A” ( k = 2), “T, C, G, A, C” (k = 3), “A, G, C, T, C” (k = 4), “A, G, T, A, C” The evaluation score decreases in the order of (k = 5). That is, it represents the similarity (accessibility) of the comparison data string to the reference data string.
[0050]
As described above, according to the present invention, an objective evaluation that is difficult with the conventional method can be performed. For example, the comparison data string “T, C, G, A, C” of k = 3 and the comparison data string “A, G, C, T, C” of k = 4 are conventionally used as the reference data string. Although it was difficult to determine whether they are close, if the similarity is determined from the viewpoint of the distance of the data constituting each comparison data string, it is objective that the comparison data string of k = 3 is closer to the reference data string It becomes possible to judge automatically.
[0051]
[Sixth embodiment]
By further applying the present invention, it is possible to extract a common data string portion from a plurality of data strings.
For example, it is assumed that there are four data strings of data string 1: “ABCCC”, data string 2: “BBCCA”, data string 3: “CABBC”, and data string 4: “ABCCB”.
Therefore, in the same manner as described above, these data strings 1 to 4 are decomposed into two data sets including the distance.
This is shown in FIG. The number between letters means the distance between two letters. For example, when there are two characters between B and C, the distance is “2”.
[0052]
A processing procedure in the sixth embodiment will be described with reference to the block diagram of FIG. 2 and the flowchart of FIG.
First, a plurality of data strings to be compared (in this case, four data strings) are input (step S21). The input / output processing unit 12 of the evaluation apparatus in FIG. 2 stores the data strings 1 to 4 in the first storage area 14a. Further, the input / output processing unit 12 decomposes each data string 1 to 4 into two data sets (step S22), attaches distance information between the data for each set, and stores them in the second storage area 14b. Store (step S23).
[0053]
The comparison calculation unit 13 reads out a data set for each of the data strings 1 to 4 from the second storage area 14b, and determines whether or not the arrangement order matches the distance between the data (step S24). In this case, for example, based on each data set of the data string 1, a matching data set is extracted from the data sets of the other data strings 2 and 3 (step S25). Then, the matched data set is stored in the third storage area 14c together with the distance between the data of each set (step S26).
[0054]
Thereafter, in response to the necessity or request for restoration (step S27), the contents stored in the third storage area 14c are restored and displayed on the display unit 15 such as a display (step S26). Thereby, it can be easily understood that the common part of these four data strings 1 to 4 is “BBC” (see the column “Shared sequence” in FIG. 17).
[0055]
[Seventh embodiment]
In the seventh embodiment, it is possible to consider the position information of the first character. In the seventh embodiment shown in FIG. 19, the position information of the first character is represented by numerical values “1” to “4” added in front of the first character. By storing this position information in the third storage area 14c together with the distance between the data, and restoring the shared array in the same manner as described above, at which position in the long data string the common part exists Can know.
[0056]
[Eighth embodiment]
The seventh embodiment can be applied even when the length of the data string is increased. For example, the human (Homo sapiens) amino acid sequence “MIVFVRFNSSHGF”PVEVDSDTSIFQ ... "and the amino acid sequence" MENNREG "of the larvae (Arabidopsis thaliana)PYSVIt becomes possible to easily find the common part with "LTRDQLKGNMKKQIA ...".
Also in this case, the amino acid sequences (data strings) for humans and worms are decomposed into sets of two data having position information in each data string and distance information between the data.
[0057]
For example, when comparing the above human amino acid sequence with the amino acid sequence of the worm, the 14th P from the beginning of the human amino acid sequence is shown. V (“13P2V”) and the 8th P in the amino acid sequence of the worm V (“8P2V”) is common.
In the seventh and eighth embodiments described above, basically, the same processing as in the sixth embodiment may be performed. In the seventh and eighth embodiments, processing is performed according to the procedure shown in FIG.
[0058]
In the flowchart of FIG. 20, the same steps as those in the flowchart of FIG. 18 are denoted by the same reference numerals, and the description thereof is omitted.
In the processing of the seventh and eighth embodiments, after extracting a set of two data (step S22), when assigning distance information (step S23), the position information of the set of data is temporarily stored. The data is stored in a storage unit (for example, the third storage area 14c) (step S31). In step S25, when the matching data set is extracted and stored in the storage unit together with the distance information, the position information is read from the storage unit and added to the data set (step 32). When the shared part is restored in step S28, only the common part is restored to a predetermined position on the amino acid sequence based on the position information. This makes it possible to easily determine the common part.
[0059]
[Ninth Embodiment]
The present invention can also be effectively used to detect a data sequence in a certain arrangement order such as an amino acid sequence motif.
The amino acid motif sequence is, for example, a data string composed of a plurality of data (generally characters) such as C ... H ... C ... and prescribed data (C, H, C). The distance between is within a certain range. That is, a certain amino acid sequence motif can be represented as C4-14H4-15C3-5C, for example.
[0060]
In the analysis of the amino acid sequence motif, the amino acid sequence motif is used as a reference data string, and whether or not a data string common to the reference data string exists in the comparison data string (amino acid sequence) is analyzed.
In this case, first, a data set having the same order as the reference data string is extracted from the comparison data string (in the example of the table below, a data set having the CHCC order is extracted. To do).
Then, as shown in the table below, the distance information of the reference data is given a width, and the distance information is included in the range of the distance information of the reference data string for each group in the same order in the comparison data string. To determine whether or not
[0061]
[Table 1]

[0062]
Then, when the distance information matches for all of the data sets in the comparison data string (that is, when the evaluation score is 1 in the above table), it is determined that the predetermined motif exists in the comparison data string To do. In the example of the above table, it can be determined that the motif does not exist in the comparison data string 1 but the motif exists in the comparison data string 2.
[0063]
Although a preferred embodiment of the present invention has been described, the present invention is not limited to the above-described embodiment.
For example, in the above description, for convenience of explanation, the method for evaluating the similarity between the reference data string and the comparison data string has been described. However, the array data is arranged in two-character array data (for example, C__T) for evaluating the similarity. Position information (= i) is added, and the distance between 'C' and 'T' is quantified (= w), and one minimum core sequence data is converted into “iCwT”, for example, “1C2T”. By expressing and memorizing like
(1) It becomes possible to output continuous character array data shared by the reference data string and the comparison data string.
{Circle around (2)} Similarly to {circle around (1)}, it is possible to output a unique continuous character array of each of the reference data string and the comparison array data.
(3) A single base substitution sequence (SNP), which is an important issue in gene analysis, can be reliably grasped.
[0064]
In addition, it can be the basis of an objective, reliable and efficient analysis method for DNA sequence analysis.
Further, in the present invention, it is possible to store a program for executing the processing described above in a recording medium such as an optical disk or a magnetic disk, and read the program read from the recording medium into a computer for execution.
Furthermore, in this invention, it is possible to implement combining 1st embodiment-9th embodiment suitably. For example, after extracting a common part from a plurality of data strings according to the sixth embodiment, according to the first embodiment, the consistency of the data arrangement order is determined for the data string consisting of the common part. It is also possible to do so.
Further, the present invention is not limited to the one-dimensional data string as described above, but can be applied to a two-dimensional data string, and can also be applied to pattern analysis for determining the similarity of comparison images. .
[0065]
【The invention's effect】
As described above, according to the present invention, the similarity and commonality of data strings can be objectively evaluated by a simple method. Furthermore, even if the number of data increases, only a set of two data is extracted, and an objective evaluation is performed without imposing an excessive burden on the processing power of a computer without requiring an excessively complicated processing process. It can be performed inexpensively and in a short time. Therefore, it is possible to perform evaluation between character strings of a certain scale even with processing by a general-purpose computer such as a personal computer, and it is also possible to distribute processing and perform parallel processing with a plurality of computers.
[Brief description of the drawings]
FIG. 1 is a flowchart illustrating an evaluation method of the present invention.
FIG. 2 is a block diagram showing a configuration of an apparatus for executing the evaluation method of the present invention.
FIG. 3 is a specific example according to the first embodiment of the evaluation method of the present invention, and shows evaluation results of comparison data strings “A, B, C, D, E” with k = 1.
FIG. 4 is a specific example according to the first embodiment of the evaluation method of the present invention, and shows evaluation results of comparison data strings “A, C, B, D, E” with k = 2.
FIG. 5 is a specific example according to the first embodiment of the evaluation method of the present invention, and shows the evaluation results of the comparison data string “C, B, A, E, D” for k = 3.
FIG. 6 is a specific example according to the first embodiment of the evaluation method of the present invention, and shows the evaluation results of the comparison data string “E, A, B, D, C” with k = 4.
FIG. 7 is a specific example according to the first embodiment of the evaluation method of the present invention, and shows the evaluation result of the comparison data string “E, D, C, B, A” with k = 5.
FIG. 8 is a table showing the results of similarity evaluation according to the second embodiment.
FIG. 9 is a table showing the results of similarity evaluation according to the third embodiment.
FIG. 10 is a table showing the results of similarity evaluation according to the fourth embodiment.
FIG. 11 is a table showing the results of similarity evaluation according to the fifth embodiment.
FIG. 12 is a specific example according to the fifth embodiment of the evaluation method of the present invention and shows the evaluation result of the comparison data string “C, T, C, G, A” with k = 1.
FIG. 13 is a specific example according to the fifth embodiment of the evaluation method of the present invention, and shows the evaluation result of the comparison data string “C, T, T, G, A” with k = 2.
FIG. 14 is a specific example according to the fifth embodiment of the evaluation method of the present invention and shows the evaluation result of the comparison data string “T, C, G, A, C” with k = 3.
FIG. 15 is a specific example according to the fifth embodiment of the evaluation method of the present invention, and shows the evaluation results of the comparison data string “A, G, C, T, C” with k = 4.
FIG. 16 is a specific example according to the fifth embodiment of the evaluation method of the present invention, and shows the evaluation results of the comparison data string “A, G, T, A, C” with k = 5.
FIG. 17 is a table showing a result of a process for detecting an array portion shared by data strings according to the sixth embodiment.
FIG. 18 is a flowchart for explaining a processing procedure according to the sixth embodiment;
FIG. 19 is a table showing a result of a process for restoring an array shared by a data string according to the seventh embodiment as an original array;
FIG. 20 is a flowchart for explaining a processing procedure of the seventh and eighth embodiments;
[Explanation of symbols]
1 Evaluation device
11 Input section
13 Comparison / Calculation section
14 Storage unit
14a First storage area
14b Second storage area
14c Third storage area
15 Display section

Claims (10)

In an evaluation apparatus for evaluating how similar comparison data consisting of similar data is to a reference data string consisting of a plurality of character, numerical value, symbol or figure data,
Accepts input of a reference data string composed of a plurality of character, numerical value, symbol or graphic data, or a reference data string formed by combining these data , stores the received data in the storage unit, and accepts input of the comparison data string, and stores the data An input unit stored in
From each of the reference data sequence and the comparison data sequence stored in the storage unit, a set of two data is formed without changing the arrangement order, and stored in the storage unit, and stored in the storage unit A comparison unit that compares the arrangement order of the data in the set of comparison data strings and the arrangement order of the data of the group in which the data constituting the set in the reference data stored in the storage unit is the same data ; ,
As a result of comparison, when the arrangement order matches, a first evaluation score is assigned, and when the arrangement order does not match, a second evaluation score is assigned, and for all sets extracted from the comparison data string A total of the attached first and second evaluation scores, storing the obtained total score in the storage unit, and performing an evaluation based on the total score ;
An apparatus for evaluating a data string composed of characters or the like characterized by comprising:   The data string evaluation device according to claim 1, wherein 1 is assigned as the first evaluation score, and 0 is assigned as the second evaluation score. In an evaluation apparatus for evaluating how similar comparison data consisting of similar data is to a reference data string consisting of a plurality of character, numerical value, symbol or figure data,
Accepts input of a reference data string composed of a plurality of character, numerical value, symbol or graphic data, or a reference data string formed by combining these data , stores the received data in the storage unit, and accepts input of the comparison data string, and stores the data An input unit stored in
From the reference data string and comparison data string stored in the storage unit, a set of two data is formed and stored in the storage unit, and the data in the comparison data string set stored in the storage unit A comparison unit that compares the arrangement order of the data and the arrangement order of the data of the set in which the data constituting the set in the reference data stored in the storage unit is the same data ;
The number of pairs in which the arrangement order in the set of comparison data strings matches or the number of sets that do not match is obtained, and the comparison data is calculated from the ratio of the number of sets that match or do not match with respect to the number of all sets. Calculating an evaluation value of a column, and storing the evaluation value in the storage unit ;
An apparatus for evaluating a data string composed of characters or the like characterized by comprising: In the data string evaluation device according to any one of claims 1 to 3,
From each of the plurality of data strings input from the input unit, without changing the arrangement order, forming a set consisting of two data and storing in the storage unit,
From the sets stored in the storage unit, a set in which the arrangement order of the data matches in the plurality of data strings is extracted, and the matching set is extracted from the data string for each of the data strings. is stored in the storage unit together with the position information,
For each data string, having a calculation unit that reproduces a set in which the arrangement order and the position information match based on information stored in the storage unit,
A data string evaluation device composed of characters or the like characterized by   4. The data string evaluation device according to claim 1, wherein the arrangement order includes a distance between the two data.   The data constituting the reference data string and the comparison data string is a base sequence of a gene consisting of four types of character data of A (adenine), G (guanine), T (thymine) and C (cytosine). An apparatus for evaluating a data string comprising characters or the like according to any one of claims 1 to 5 as a characteristic data string.   The data according to any one of claims 1 to 5, wherein the data constituting the reference data string and the comparison data string is a character or the like according to 20 amino acid sequences constituting a protein. A data string evaluation device comprising: In a computer program for a data string evaluation apparatus for evaluating how similar comparison data consisting of similar data is to a reference data string consisting of a plurality of character, numerical value, symbol or figure data,
Accepts input of a reference data string composed of a plurality of character, numerical value, symbol or graphic data, or a reference data string formed by combining these data, stores the received data in the storage unit, and accepts input of the comparison data string, and stores the data Storing in the step,
From the reference data and the comparison data string stored in the storage unit, without changing the arrangement order, forming a set of two data , and storing in the storage unit ;
And order of the data in the set of said comparison data string stored in the storage unit, the order of the set of data data constituting the set are the same data in the reference data stored in the storage unit A step of comparing
When the arrangement order is matched, a first evaluation score is assigned, and when the arrangement order is not matched, a second evaluation score is added , and stored in the storage unit ;
Summing the first and second evaluation scores attached to all sets extracted from the comparison data, and storing the obtained total score in the storage unit ;
A computer program for a data string evaluation apparatus, characterized in that In a computer program for a data string evaluation apparatus for evaluating how similar comparison data consisting of similar data is to a reference data string consisting of a plurality of character, numerical value, symbol or figure data,
Accepts input of a reference data string composed of a plurality of character, numerical value, symbol or graphic data, or a reference data string formed by combining these data, stores the received data in the storage unit, and accepts input of the comparison data string, and stores the data Storing in the step,
From the reference data string and comparison data string stored in the storage unit, forming a set of two data , and storing in the storage unit ;
And order of the data in the set of said comparison data string stored in the storage unit, the order of the set of data data constituting the set are the same data in the reference data stored in the storage unit A step of comparing
Obtaining the number of sets in which the arrangement order in the set of comparison data strings coincides or the number of sets in which they do not match;
Obtaining the evaluation value of the comparison data string from the ratio of the number of matching or non-matching pairs to the number of all pairs, and storing the evaluation value in the storage unit ;
A computer program for a data string evaluation apparatus, characterized in that In the computer program for the data string evaluation device according to claim 9 or 10,
From each of the plurality of data strings input from the input unit, without changing the arrangement order, forming a set of two data and storing in the storage unit;
Extracting a set in which the arrangement order of the data matches in the plurality of data strings from the set stored in the storage unit ;
Storing the matched set for each of the data strings together with location information in the data string in a storage unit;
For each data string, reproducing the set in which the arrangement order and the position information match based on information stored in the storage unit;
A computer program for a data string evaluation apparatus, characterized in that

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