CN103995983B - A kind of method of logic-based model analysis Signaling transduction networks interior joint importance - Google Patents
A kind of method of logic-based model analysis Signaling transduction networks interior joint importance Download PDFInfo
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Abstract
The invention discloses a kind of method of logic-based model analysis Signaling transduction networks interior joint importance.The method is comprised the following steps：S1, according to the signal transduction pathway stored in database, builds a Signaling transduction networks；S2, Signaling transduction networks are expressed as the series and parallel model of logic according to the annexation between Signaling transduction networks interior joint；S3, the general structure to Signaling transduction networks is decomposed into most basic series connection and parallel-connection structure；S4, when the fault rate of the individual node in node or multiple nodes changes, the probability change value that Signaling transduction networks break down is calculated, the probability broken down by Signaling transduction networks changes value metric individual node or multiple nodes to keeping the importance of Signaling transduction networks function.Whole network structure is modeled by logical model, is conducive to being investigated from global network topology attribute angle the importance of individual node.
Description
Technical field
The present invention relates to bioinformatics technique field, turn in particular to a kind of logic-based model analysis signal
The method for leading node importance in network.
Background technology
In Signaling transduction networks, weighing the importance of single protein helps to find to be closed during cell signalling
The protein of key and the weak link of biosystem, the discovery of crucial protein and the weak link of biosystem will have
Help people and preferably recognize organism, it will help the screening and research and development of some medicines.At present, in Signaling transduction networks moderate
The method for measuring protein importance is also less.
Biologically, the corresponding gene necessity of further important node is higher, and further important node has slower
Evolutionary rate, in this way need to carry out more experimental study weighing protein importance, and be difficult to be quantified
Analysis.In protein-protein interaction network, Connected degree is the topological index of the most frequently used description protein importance.Node
Connected degree refers to the number of all nodes that can be interacted with the node.Usual Connected degree node higher is for protecting
The overall structure and function for demonstrate,proving network are more important, but the index has only investigated the local characteristicses of node, do not consider node place
Whole network topological structure.In fact, Connected degree relatively low node in part is likely to become the bottleneck of network, when they send out
During raw failure, whole network is destructurized so that signal cannot be transmitted effectively, so as to cause the generation of disease.
Also certain methods carry out the prediction of node importance in network by the flow analysis of network.Such as article Liu
W,et al.SigFlux:a novel network feature to evaluate the importance of
proteins in signal transduction networks.BMC Bioinformatics,2006,7:515 propose
A kind of method that minimal path sets based in network predict node importance, detailed step is as follows：
1) Signaling transduction networks of hippocampus neurons in mice are downloaded from document, as network to be studied；
2) all paths between input and output are generated using breadth-first search algorithm, is searched using MFinder softwares
All of backfeed loop in rope network, obtains the minimal path sets in network；
3) a kind of new feature SigFlux for measuring single protein importance is proposed, is defined as comprising the node most
Path collection number accounts for the ratio of all minimal path sets numbers, and calculates albumen according to the distribution situation of path in network and backfeed loop
The SigFlux values of matter；
4) necessity and evolutionary rate of SigFlux and murine genes are carried out into correlation analysis, further compares SigFlux
With Connected degree index, illustrate SigFlux as the validity for weighing protein importance index.
From above-mentioned in the prior art as can be seen that its prediction node importance is mainly based upon the part of Signaling transduction networks
Topological attribute predicts the importance of individual node in network, and the important work of analysis node is not carried out from the global structure of network
With, and lack the accident analysis mechanism from probability, do not consider the raising of fault rate of individual node to whole net
Influence caused by network.
The content of the invention
The present invention is intended to provide a kind of method of logic-based model analysis Signaling transduction networks interior joint importance, to solve
Do not consider that the raising of the fault rate of individual node is asked the technology of the influence caused by whole network in the prior art certainly
Topic.
To achieve these goals, according to an aspect of the invention, there is provided a kind of logic-based model analysis signal
The method of transduction node importance in network.The method is comprised the following steps：S1, leads to according to the signal transduction stored in database
Road, builds a Signaling transduction networks；S2, according to the annexation between Signaling transduction networks interior joint by Signaling transduction networks
It is expressed as the series and parallel model of logic；S3, is decomposed into most basic series connection and and is coupled to the general structure of Signaling transduction networks
Structure；S4, when the fault rate of the individual node in node or multiple nodes changes, calculates Signaling transduction networks and event occurs
The probability change value of barrier, the probability broken down by Signaling transduction networks changes value metric individual node or multiple nodes to protecting
Hold the importance of Signaling transduction networks function.
Further, the method also includes：S5, the probability change value that Signaling transduction networks are broken down must with gene
The evolutionary rate of the property wanted and gene carries out correlation analysis, is compared with default Connected degree index, and then to Signaling transduction networks
In parameter be adjusted.
Further, in step s 4, be set in it is trouble-proof in the case of, in Signaling transduction networks each node hair
The probability of raw failure is a fixed value.
Further, in step s 4, setting under normal circumstances, will under normal circumstances in Signaling transduction networks each
The probability of nodes break down is set as a constant value, and constant value is the average of each nodes break down in Signaling transduction networks
Value, when individual node breaks down, the corresponding probability that the individual node breaks down is changed into 1, calculates each most basic string
The probability that connection and parallel-connection structure break down, and then extrapolate the probability that Signaling transduction networks break down.
Further, in step S1, various signal transduction pathway behaviours, mouse, fruit bat, the line stored in existing database
Worm or the various signal transduction pathways of yeast.
Apply the technical scheme of the present invention, whole network structure is modeled by logical model, be conducive to from the overall situation
Network topology attribute angle investigate the importance of individual node；The fault rate of individual node is analyzed from probability
Improve to the influence caused by whole network, easily carry out quantitative analysis；Can easily by the importance analysis of individual node
The joint importance analysis of multiple nodes are generalized to, the weak module in network is found.Letter can be found by the method analyzed
Important node in number transduction network, for biological experimental design provides guidance, helps study the function of nodes.
Brief description of the drawings
The Figure of description for constituting the part of the application is used for providing a further understanding of the present invention, of the invention to show
Meaning property and its illustrates, for explaining the present invention, not constitute inappropriate limitation of the present invention embodiment.In the accompanying drawings：
Fig. 1 shows the logic-based model analysis Signaling transduction networks interior joint according to an exemplary embodiment of the invention
The flow chart of the method for importance；
Saved in the logic-based model analysis Signaling transduction networks that Fig. 2 shows according to another exemplary embodiment of the invention
The flow chart of the method for point importance；
Fig. 3 A show the part of real antiapoptotic signals transduction network；
Fig. 3 B show the corresponding connection in series-parallel logical models of Fig. 3 A；
Fig. 4 A show most basic cascaded structure；And
Fig. 4 B show most basic parallel-connection structure；
Fig. 5 shows the apoptotic signal transduction network of people；
Fig. 6 shows the schematic diagram after Fig. 5 Module Divisions；
Fig. 7 shows the corresponding logic relation pictures of Fig. 6；
Fig. 8 shows the corresponding middle sub-module of module 1 in Fig. 7.
Specific embodiment
It should be noted that in the case where not conflicting, the feature in embodiment and embodiment in the application can phase
Mutually combination.Describe the present invention in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
According to a kind of typical implementation method of the present invention, there is provided saved in a kind of logic-based model analysis Signaling transduction networks
The method of point importance.The method is comprised the following steps：S1, according to the signal transduction pathway stored in database, builds one
Signaling transduction networks；Signaling transduction networks are expressed as logic by S2 according to the annexation between Signaling transduction networks interior joint
Series and parallel model；S3, the general structure to Signaling transduction networks is decomposed into most basic series connection and parallel-connection structure；S4, when upper
When the fault rate for stating individual node in node or multiple nodes changes, calculate that Signaling transduction networks break down is general
Rate change value, the probability broken down by Signaling transduction networks changes value metric individual node or multiple nodes to keeping signal
The importance of transduction network function, as shown in Figure 1.
Apply the technical scheme of the present invention, whole network structure is modeled by logical model, be conducive to from the overall situation
Network topology attribute angle investigate the importance of individual node；Connection in series-parallel relation is the base of calculating network fault rate
Plinth, big network is resolved into basic series parallel structure step by step could calculate whole net according to the probability of malfunction of all nodes
The probability of malfunction of network, so as to the raising of the fault rate of analysis individual node from probability is to the shadow caused by whole network
Ring, a situation arises compare identical with actual disease, easily carries out quantitative analysis；Can easily by the importance of individual node
Analysis is generalized to the joint importance analysis of multiple nodes, finds the weak module in network.
For complicated Signaling transduction networks, it is relatively difficult to be directly changed into logical relation model.Its is basic
Thinking is to divide complex network step by step：The first step is to be divided into separate multiple modules；Second step is by by
The module that one step is obtained continues to divide, and its internal connection in series-parallel relation is distinguished, if inside modules can distinguish individual node
Connection in series-parallel relation, then the logical relation model conversion of the module terminate, otherwise continue to be divided the module, be divided into multiple
Independent fritter, repeats partiting step；It is finally that will be spliced by the logical relation model in each module, forms final patrolling
Collect relational model.
Preferably, as shown in Fig. 2 method is further included：S5, the probability change value that Signaling transduction networks are broken down
Correlation analysis is carried out with the necessity of gene and the evolutionary rate of gene, is compared with default Connected degree index, and then to letter
Number transduction network in parameter be adjusted, so as to be more beneficial for obtaining gratifying result, i.e., with biological data kissing
Close, it is such as consistent with gene necessity.Wherein, the data such as necessity and evolutionary rate of gene use existing biological data storehouse
In information, such as mouse data whose necessity store in MGD.Wherein, default Connected degree index is according in existing database
Information obtain.
According to a kind of typical implementation method of the present invention, in step s 4, set under normal circumstances, Signaling transduction networks
In the probability of each nodes break down be a fixed value, so facilitate the calculating of follow-up probability.For example, in step s 4,
The probability of each nodes break down in Signaling transduction networks under normal circumstances is set as a constant value, constant value is signal
The average value of each nodes break down in transduction network, when individual node breaks down, what the individual node broke down
Correspondence probability is changed into 1, calculates the probability that each most basic series connection and parallel-connection structure break down, and then extrapolate signal transduction
The probability of network failure.Wherein, refer under normal circumstances in the case that Signaling transduction networks can normally transduce.
The method of logic-based model analysis Signaling transduction networks interior joint importance of the invention can be used for various things
The various signal transduction pathways of the assessment of signal transduction pathway in kind, such as people, mouse, fruit bat, nematode or yeast.
In of the invention one typical implementation method, the logic-based model analysis Signaling transduction networks interior joint is important
The method of property is comprised the following steps：
1. the structure of Signaling transduction networks and logical model is expressed as
For Signaling transduction networks, the annexation existed between the node in network forms topological structure.By whole
Individual network structure ensures effective transmission of signal, especially by the redundancy scheme of path, it is ensured that the part of nodes of network occurs
During mistake (failure), network still is able to normal function.In the path, according between node with and/or pass
System, can be converted into connection in series-parallel logical model.For example, if Fig. 3 A are a real Signaling transduction networks, its is corresponding
Connection in series-parallel logical model is as shown in Figure 3 B.Here the activation between node and suppression relation are not differentiated between.
2. the probability of malfunction of whole network is calculated
For complicated connection in series-parallel logical network, most basic connection in series-parallel knot in Fig. 4 A and Fig. 4 B can be always divided into
Structure.Wherein, Fig. 4 A show most basic cascaded structure, and Fig. 4 B show most basic parallel-connection structure.
For cascaded structure, if the corresponding fault rate of node A, B, C is respectively P (A), P (B) and P (C), then
The probability that the train G being made up of these three nodes breaks down is：
P (G)=1- [1-P (A)] [1-P (B)] [1-P (C)] (1)
The probability that the parallel system R being made up of these three nodes breaks down is：
P (R)=P (A) P (B) P (C) (2)
Basic connection in series-parallel module is divided into by by complication system, can be according to the fault rate meter of individual node
Calculate the probability that whole system breaks down.
By basic module calculate total breakdown probability process divided with prior module the step of be it is opposite, before be by
Big network is divided into small module step by step, then calculates probability of malfunction by small module here, step by step extension module scope,
Until calculating the probability of malfunction of whole network comprising whole network.
3. importance measures of individual node
It is assumed that under normal circumstances, the probability that each node i breaks down in network is a fixed value, such as P (i)=
0.5, according to the logical model of network, whole system S can be calculated0Total probability P (the S for breaking down0)。
For the individual node i in network, when it breaks down, its correspondence probability is changed into P (i)=1.Think do not have now
There are other nodes break downs, then can calculate with this understanding, the probability of malfunction S of whole systemiP (S1), positive reason
P (S under conditioni)≧P(S0)。
The importance of node i is defined as：
F (i)=P (Si)-P(S0) (3)
The value characterizes node i and breaks down the impact probability broken down to whole network, is commented such that it is able to quantitative
Estimate importance of the node for whole network structure.
4. many importance measures of node
Importance measures with individual node are similar, it is assumed that n node { 1 ..., n } while break down, its node
Probability of malfunction is changed into P (i)=1, and i=1 ..., n can be calculated with this understanding, the P of the probability of malfunction Sn of whole system
(Sn).The joint importance of this n node is defined as：
F (n)=P (Sn)-P(S0) (4)
It is noted that the joint importance is not equivalent to the n superposition of the independent importance of node, and with this n node
Distribution and connection have close ties.
Beneficial effects of the present invention are further illustrated below in conjunction with embodiment, it is following the step of be not particularly described,
Can be realized using ordinary skill in the art means.
Embodiment 1
1) according to the various signal transduction pathways stored in existing database, the apoptotic signal transduction network of people is built, such as
Shown in Fig. 5.For the apoptotic signal transduction network of people as shown in Figure 5, Module Division and logical relation conversion are carried out to it.
2) Fig. 5 is divided into separate module 1 and module 2, as shown in Figure 6.
3) logical relation division is carried out according to Fig. 6, obtains corresponding logic relation picture, as shown in Figure 7.
4) under normal circumstances, the fault rate of individual node is a constant value (such as 0.1), according to logical relation for setting
Figure, can calculate the fault rate of whole network.Its computational methods is first to calculate the fault rate in each module,
Then the fault rate of whole network is obtained.For module 1, middle sub-module can be marked off, as shown in Figure 8.
First calculate the fault rate P of middle sub-modulem,
Pm=0.1 [1- (1-0.1) (1-0.01)] [1- (1-0.1) (1-0.01)]=0.0012
Then comprehensively obtaining whole module probability is：
P(M1)=1- (1-0.1) { 1-Pm(1-0.1)=0.1910
For module 2, it is 5 series connection of node, and corresponding probability of malfunction is：
P(M2)=1- (1-0.1)5=0.4095
Network failure probability of happening P (S always can finally be obtained0)=0.2241, calculates more complicated herein, may be programmed and realizes.
When wherein certain node i breaks down, it is 1 that its failure changes, and repeats above calculating process, obtains new
Fault rate P (Si), the importance of individual node is then weighed according to its difference.
For the network, Caspase3 nodes are mostly important, and its importance score value is 1.The importance of other nodes
Probability is respectively less than 1, and such as Caspase9, its importance score value is 0.5738.
Similar, can be with computing module 1 and the importance score value of module 2.
From above-described embodiment as can be seen that at least being had the advantages that using technical scheme：
1st, whole network structure is modeled by logical model, is conducive to coming from global network topology attribute angle
Investigate the importance of individual node；
2nd, the raising of fault rate of individual node is analyzed from probability to the influence caused by whole network, with reality
The disease on border a situation arises relatively coincide, easily carry out quantitative analysis；
The 3rd, the importance analysis of individual node can be easily generalized to the joint importance analysis of multiple nodes, found
Weak module in network.
The preferred embodiments of the present invention are the foregoing is only, is not intended to limit the invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.It is all within the spirit and principles in the present invention, made any repair
Change, equivalent, improvement etc., should be included within the scope of the present invention.
Claims (4)
1. a kind of method of logic-based model analysis Signaling transduction networks interior joint importance, it is characterised in that including following
Step：
S1, according to the various signal transduction pathways stored in existing database, builds a Signaling transduction networks；
The Signaling transduction networks are expressed as logic by S2 according to the annexation between the Signaling transduction networks interior joint
Series and parallel model；
S3, the general structure to the Signaling transduction networks is decomposed into most basic series connection and parallel-connection structure；
S4, when the fault rate of the individual node in the node or multiple nodes changes, calculates the signal transduction
The probability change value of network failure, the probability broken down by the Signaling transduction networks changes single described in value metric
Node or the multiple node are to keeping the importance of the Signaling transduction networks function；
S5, the probability change value that the Signaling transduction networks are broken down is entered with the necessity of gene and the evolutionary rate of gene
Row correlation analysis, is compared, and then the parameter in the Signaling transduction networks is adjusted with existing Connected degree index.
2. method according to claim 1, it is characterised in that in the step S4, be set in trouble-proof feelings
Under condition, the probability of each nodes break down is a fixed value in the Signaling transduction networks.
3. method according to claim 2, it is characterised in that in the step S4, setting is under normal circumstances, described
The probability of each nodes break down is 0.5 in Signaling transduction networks, and when individual node breaks down, its correspondence probability is changed into
1, the probability that each most basic series connection and parallel-connection structure break down is calculated, and then extrapolate the Signaling transduction networks
The probability for breaking down.
4. method according to claim 1, it is characterised in that in the step S1, what is stored in existing database is various
The various signal transduction pathways of signal transduction pathway behaviour, mouse, fruit bat, nematode or yeast.
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