US20080302957A1 - Identifying ions from mass spectral data - Google Patents

Identifying ions from mass spectral data Download PDF

Info

Publication number
US20080302957A1
US20080302957A1 US12/131,888 US13188808A US2008302957A1 US 20080302957 A1 US20080302957 A1 US 20080302957A1 US 13188808 A US13188808 A US 13188808A US 2008302957 A1 US2008302957 A1 US 2008302957A1
Authority
US
United States
Prior art keywords
peak shape
isotope
shape function
ions
mass spectral
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US12/131,888
Other languages
English (en)
Inventor
Yongdong Wang
Ming Gu
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Cerno Bioscience LLC
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to US12/131,888 priority Critical patent/US20080302957A1/en
Publication of US20080302957A1 publication Critical patent/US20080302957A1/en
Assigned to CERNO BIOSCIENCE LLC reassignment CERNO BIOSCIENCE LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: GU, MING, WANG, YONGDONG
Abandoned legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J49/00—Particle spectrometers or separator tubes
    • H01J49/0009—Calibration of the apparatus
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J49/00—Particle spectrometers or separator tubes
    • H01J49/0027—Methods for using particle spectrometers
    • H01J49/0036—Step by step routines describing the handling of the data generated during a measurement
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01D—SEPARATION
    • B01D59/00—Separation of different isotopes of the same chemical element
    • B01D59/44—Separation by mass spectrography

Definitions

  • the present invention relates to mass spectrometry systems. More particularly, it relates to mass spectrometry systems that are useful for the analysis of complex mixtures of molecules, including large and small organic molecules such as proteins or peptides, environmental pollutants, pharmaceuticals and their metabolites, and petrochemical compounds, to methods of analysis used therein, and to a computer program product having computer code embodied therein for causing a computer, or a computer and a mass spectrometer in combination, to affect such analysis.
  • Accurate line shape calibration provides a highly reliable metric to assist in unambiguous formula identification by matching the measured spectra to calculated candidate formulas, as in International Patent Application PCT/US2005/039186, filed on Oct. 28, 2005.
  • An additional aspect of the invention is, in general, a computer readable medium having thereon computer readable code for use with a mass spectrometer system having a data analysis portion including a computer, the computer readable code being for causing the computer to analyze data by performing the methods described herein.
  • the computer readable medium preferably further comprises computer readable code for causing the computer to perform at least one of the specific methods described.
  • the invention is also directed generally to a mass spectrometer system for analyzing chemical composition, the system including a mass spectrometer portion, and a data analysis system, the data analysis system operating by obtaining calibrated continuum spectral data by processing raw spectral data; generally in accordance with the methods described herein.
  • the data analysis portion may be configured to operate in accordance with the specifics of these methods.
  • the mass spectrometer system further comprises a sample preparation portion for preparing samples to be analyzed, and a sample separation portion for performing an initial separation of samples to be analyzed.
  • the separation portion may comprise at least one of an electrophoresis apparatus, a chemical affinity chip, or a chromatograph for separating the sample into various components.
  • FIG. 1 is a block diagram of a mass spectrometer in accordance with the invention.
  • FIG. 2 is flow chart of the steps in the identification of isotopically similar ions used by the system of FIG. 1 .
  • FIG. 3A to FIG. 3F are graphical representations of the some results obtained during the process of FIG. 2 .
  • FIG. 1 there is shown a block diagram of an analysis system 10 , that may be used to analyze proteins or other molecules, as noted above, incorporating features of the present invention.
  • an analysis system 10 that may be used to analyze proteins or other molecules, as noted above, incorporating features of the present invention.
  • FIG. 1 a block diagram of an analysis system 10 , that may be used to analyze proteins or other molecules, as noted above, incorporating features of the present invention.
  • the present invention will be described with reference to the single embodiment shown in the drawings, it should be understood that the present invention can be embodied in many alternate forms of embodiments. In addition, any suitable types of components could be used.
  • the Analysis system 10 has a sample preparation portion 12 , other detector portion 23 , a mass spectrometer portion 14 , a data analysis system 16 , and a computer system 18 .
  • the sample preparation portion 12 may include a sample introduction unit 20 , of the type that introduces a sample containing proteins, peptides, or small molecule drug of interest to system 10 , such as Finnegan LCQ Deca XP Max, manufactured by Thermo Electron Corporation of Waltham, Mass., USA.
  • the sample preparation portion 12 may also include an analyte separation unit 22 , which is used to perform a preliminary separation of analytes, such as the proteins to be analyzed by system 10 .
  • Analyte separation unit 22 may be any one of a chromatography column, an electrophoresis separation unit, such as a gel-based separation unit manufactured by Bio-Rad Laboratories, Inc. of Hercules, Calif., and is well known in the art.
  • a voltage is applied to the unit to cause the proteins to be separated as a function of one or more variables, such as migration speed through a capillary tube, isoelectric focusing point (Hannesh, S. M., Electrophoresis 21, 1202-1209 (2000), or by mass (one dimensional separation)) or by more than one of these variables such as by isoelectric focusing and by mass.
  • An example of the latter is known as two-dimensional electrophoresis.
  • the mass spectrometer portion 14 may be a conventional mass spectrometer and may be any one available, but is preferably one of MALDI-TOF, quadrupole MS, ion trap MS, qTOF, TOF/TOF, or FTMS. If it has a MALDI or electrospray ionization ion source, such ion source may also provide for sample input to the mass spectrometer portion 14 .
  • mass spectrometer portion 14 may include an ion source 24 , a mass analyzer 26 for separating ions generated by ion source 24 by mass to charge ratio, an ion detector portion 28 for detecting the ions from mass analyzer 26 , and a vacuum system 30 for maintaining a sufficient vacuum for mass spectrometer portion 14 to operate efficiently. If mass spectrometer portion 14 is an ion mobility spectrometer, generally no vacuum system is needed and the data generated are typically called a plasmagram instead of a mass spectrum.
  • This other detector portion 23 may be a single channel UV detector, a multi-channel UV spectrometer, or Reflective Index (RI) detector, light scattering detector, radioactivity monitor (RAM) etc.
  • RI Reflective Index
  • RAM radioactivity monitor
  • the data analysis system 16 includes a data acquisition portion 32 , which may include one or a series of analog to digital converters (not shown) for converting signals from ion detector portion 28 into digital data.
  • This digital data is provided to a real time data processing portion 34 , which processes the digital data through operations such as summing and/or averaging.
  • a post-processing portion 36 may be used to do additional processing of the data from real time data processing portion 34 , including library searches, data storage and data reporting.
  • Computer system 18 provides control of sample preparation portion 12 , mass spectrometer portion 14 , other detector portion 23 , and data analysis system 16 , in the manner described below.
  • Computer system 18 may have a conventional computer monitor or display 40 to allow for the entry of data on appropriate screen displays, and for the display of the results of the analyses performed.
  • Computer system 18 may be based on any appropriate personal computer, operating for example with a Windows® or UNIX® operating system, or any other appropriate operating system.
  • Computer system 18 will typically have a hard drive 42 , on which the operating system and the program for performing the data analysis described below is stored.
  • a drive 44 for accepting a CD or floppy disk is used to load the program in accordance with the invention on to computer system 18 .
  • Data analysis system 16 may be a program written to implement the processing steps discussed below, in any of several programming languages such as C++, JAVA or Visual Basic.
  • ⁇ circle around ( ⁇ ) ⁇ represents convolution
  • g represents a small Gaussian
  • p represents the mass spectral peak shape function.
  • the true peak shape function p can be directly obtained without iteration, and the relative concentrations c 1 and c 2 can be obtained from the above Equation 4 in a single step.
  • the true peak shape function p may proceed with the mass spectral calibration as referenced in U.S. Pat. No. 6,983,213 to calibrate for the mass axis while also transforming the peak shape into a desired or target peak shape function that is mathematically definable.
  • Step 240 in FIG. 2 One can now move to the next stage, Step 240 in FIG. 2 , to construct an ion pattern to be searched in the rest of the mass spectral data for the possible presence of similar or “resembling” ions that would also show similar isotope patterns.
  • This is useful for researchers in the drug metabolism area where a parent drug along with its unique isotope pattern gives rise to various metabolites exhibiting similarly unique isotope patterns.
  • the unique isotope pattern may come from the parent drug itself due to the presence of Br or Cl elements in its elemental composition, or from the mixing of the native drug with its isotope labeled version.
  • the metabolites contain the same number of Br or Cl elements as the drug itself and the drug metabolism pathway is indifferent with respect to certain isotopes (which is the case in most applications), similar isotope patterns will be observed for the metabolites. Since various metabolites come at different masses and chromatographic retention times, it is difficult and time consuming to spot these isotope patterns in a typical LC/MS run that generates a data matrix on the order of 4000 time points by 8000 mass points in the presence of matrix and background ions typical of biological samples.
  • This isotope pattern t can be used to fit to a segment of mass spectral data r through the following model
  • r is an (n ⁇ 1) matrix of the profile mode mass spectral data, digitized at n m/z values;
  • c is a (k ⁇ 1) matrix of regression coefficients which are representative of the concentrations of k components in matrix K;
  • K is an (n ⁇ k) matrix composed of profile mode mass spectral responses for the k components, all sampled at the same n m/z points as r; and
  • e is an (n ⁇ 1) matrix of a fitting residual with contributions from random noise and any systematic deviations from this model.
  • the k columns of the matrix K will contain the isotope pattern t (for example, in its first column, without the loss of generality, for easy subsequent description) and any background or baseline components, which may or may not vary with mass (as additional columns).
  • K + (dimensioned as k ⁇ n) is the pseudo inverse of the matrix K, a process well established in matrix algebra, as referenced in U.S. Pat. No. 6,983,213; International Patent Application PCT/US2004/013096, filed on Apr. 28, 2004; U.S. patent application Ser. No. 11/261,440, filed on Oct. 28, 2005; International Patent Application PCT/US2005/039186, filed on Oct. 28, 2005; and International Patent Application PCT/US2006/013723, filed on Apr. 11, 2006.
  • each row in K + serves as a digital filter applied to the mass spectral segment r to arrive at a concentration vector c containing the contribution of each component, including the ion isotope pattern t and any components included in matrix K.
  • These digital filters in K + can be calculated once in a limited mass spectral range and then applied to a mass spectral segment in an extended mass range in a sliding window, much like a convolution filter, in Step 240 in FIG. 2 , to generate a concentration vector c from Equation 7 for each retention time and mass location combination.
  • This residual vector can be further reduced into a scalar by taking the 2-norm, i.e., the square root of the sum of squares of all elements involved, or root mean square error, and converted into a relative residual error as
  • this residual error While one can relate this residual error directly to the likelihood for the presence of a resembling ion, it may be more convenient intuitively to convert this residual error into a numeric metric that increases when the measured isotope pattern more closely resembles the given isotope pattern t given in Equation 5.
  • This numeric metric may be equal to the t-statistic or one minus the p-value as disclosed in U.S. Pat. No. 6,983,213 and U.S. patent application Ser. No. 11/754,305, filed on May 27, 2007; corresponding to International Patent Application PCT/US2007/069832, filed on May 28, 2007, or some other appropriate function of the residual error. This corresponds to Step 280 in FIG. 2 .
  • FIG. 3A shows the average of a few mass spectral scans from a retention time window corresponding to a faint radioactivity monitor (RAM) signal and
  • FIG. 3B shows a corresponding resemblance weight factor calculated as:
  • r i and e i are the mass spectral raw signal and residual corresponding to mass spectral data point i based on the above calculations using a mass spectral segment centered around mass spectral data point i
  • a is a user-settable parameter that takes on the form of:
  • the process described above includes a fairly comprehensive series of steps, for purposes of illustration, and to be complete. However, there are many ways in which the process may be varied, including leaving out certain steps, or performing certain steps before hand or “off-line”. For example, it is possible to follow all the above approaches by including disjoining isotope segments (segments that are not continuous with respect to one another, but have spaces between them in the spectrum), especially with data measured from higher resolution MS systems, so as to avoid the mass spectrally separated interference peaks that are located within, but are not directly overlapped, with the isotope cluster of an ion of interest.
  • Equation 1 to 8 its mathematical equivalence such as digital filtering, convolution, deconvolution, correlation, auto-correlation, regression, optimization, and fitting may also be utilized to the same effect, as is well known by one skilled in the art of digital signal processing and numerical analysis.
  • This invention discloses an approach to calculate or calibrate the actual peak shape function in order to achieve the best possible results.
  • mass and “mass to charge ratio” are used somewhat interchangeably in connection with information or output as defined by the mass to charge ratio axis of a mass spectrometer. This is a common practice in the scientific literature and in scientific discussions, and no ambiguity will occur, when the terms are read in context, by one skilled in the art.
  • the methods of analysis of the present invention can be realized in hardware, software, or a combination of hardware and software. Any kind of computer system—or other apparatus adapted for carrying out the methods and/or functions described herein—is suitable.
  • a typical combination of hardware and software could be a general purpose computer system with a computer program that, when loaded and executed, controls the computer system, which in turn control an analysis system, such that the system carries out the methods described herein.
  • the present invention can also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein, and which—when loaded in a computer system (which in turn control an analysis system), is able to carry out these methods.
  • Computer program means or computer program in the present context include any expression, in any language, code or notation, of a set of instructions intended to cause a system having an information processing capability to perform a particular function either directly or after conversion to another language, code or notation, and/or reproduction in a different material form.
  • the invention includes an article of manufacture, which comprises a computer usable medium having computer readable program code means embodied therein for causing a function described above.
  • the computer readable program code means in the article of manufacture comprises computer readable program code means for causing a computer to effect the steps of a method of this invention.
  • the present invention may be implemented as a computer program product comprising a computer usable medium having computer readable program code means embodied therein for causing a function described above.
  • the computer readable program code means in the computer program product comprising computer readable program code means for causing a computer to effect one or more functions of this invention.
  • the present invention may be implemented as a program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for causing one or more functions of this invention.

Landscapes

  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
US12/131,888 2007-06-02 2008-06-02 Identifying ions from mass spectral data Abandoned US20080302957A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US12/131,888 US20080302957A1 (en) 2007-06-02 2008-06-02 Identifying ions from mass spectral data

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US94165607P 2007-06-02 2007-06-02
US95669207P 2007-08-18 2007-08-18
US12/131,888 US20080302957A1 (en) 2007-06-02 2008-06-02 Identifying ions from mass spectral data

Publications (1)

Publication Number Publication Date
US20080302957A1 true US20080302957A1 (en) 2008-12-11

Family

ID=40094165

Family Applications (2)

Application Number Title Priority Date Filing Date
US12/131,888 Abandoned US20080302957A1 (en) 2007-06-02 2008-06-02 Identifying ions from mass spectral data
US12/602,768 Expired - Fee Related US8803080B2 (en) 2007-06-02 2008-06-02 Self calibration approach for mass spectrometry

Family Applications After (1)

Application Number Title Priority Date Filing Date
US12/602,768 Expired - Fee Related US8803080B2 (en) 2007-06-02 2008-06-02 Self calibration approach for mass spectrometry

Country Status (5)

Country Link
US (2) US20080302957A1 (ja)
EP (1) EP2160570A4 (ja)
JP (1) JP5704917B2 (ja)
CA (1) CA2689417C (ja)
WO (1) WO2008151153A1 (ja)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080001079A1 (en) * 2006-05-26 2008-01-03 Yongdong Wang Analyzing mass spectral data
WO2019118900A1 (en) * 2017-12-14 2019-06-20 California Institute Of Technology Systems and methods for predicting and interpreting comprehensive molecular isotopic structures and uses thereof
CN111325121A (zh) * 2020-02-10 2020-06-23 浙江迪谱诊断技术有限公司 一种核酸质谱数值处理方法
US10943775B2 (en) * 2016-09-02 2021-03-09 Board Of Regents, The University Of Texas System Collection probe and methods for the use thereof
CN112771375A (zh) * 2018-06-22 2021-05-07 伊罗亚科技有限公司 校正离子源效率低下的方法使得样品间归一化成为可能
US11737671B2 (en) 2017-11-27 2023-08-29 Board Of Regents, The University Of Texas System Minimally invasive collection probe and methods for the use thereof

Families Citing this family (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5771456B2 (ja) * 2011-06-24 2015-09-02 株式会社日立ハイテクノロジーズ 質量分析方法
JP6020315B2 (ja) * 2012-04-27 2016-11-02 株式会社島津製作所 質量分析データ処理方法及び質量分析データ処理装置
WO2013169808A2 (en) * 2012-05-07 2013-11-14 Infoclinika, Inc. Preparing lc/ms data for cloud and/or parallel image computing
JP5993259B2 (ja) * 2012-09-14 2016-09-14 株式会社日立ハイテクノロジーズ 質量分析システム
US9293312B2 (en) * 2013-03-15 2016-03-22 Thermo Finnigan Llc Identifying the occurrence and location of charging in the ion path of a mass spectrometer
GB2514836B (en) * 2013-06-07 2020-04-22 Thermo Fisher Scient Bremen Gmbh Isotopic Pattern Recognition
CN106461607B (zh) * 2014-06-12 2019-10-11 株式会社岛津制作所 质谱分析用数据处理装置以及该装置用程序
US9741548B2 (en) * 2014-07-03 2017-08-22 Shimadzu Corporation Mass spectrometer
EP3523818B1 (en) * 2016-10-07 2022-08-03 Thermo Finnigan LLC System and method for real-time isotope identification
US10615015B2 (en) * 2017-02-23 2020-04-07 Thermo Fisher Scientific (Bremen) Gmbh Method for identification of the elemental composition of species of molecules
JP6839885B1 (ja) * 2018-01-09 2021-03-10 アトナープ株式会社 ピーク形状を最適化するためのシステムおよび方法
WO2019232520A1 (en) 2018-06-01 2019-12-05 Cerno Bioscience Llc Mass spectral analysis of large molecules
CN109103067B (zh) * 2018-07-20 2020-01-17 北京雪迪龙科技股份有限公司 一种提高飞行时间质谱仪灵敏度的方法
CN109271913B (zh) * 2018-09-05 2022-03-29 南京信息工程大学 一种基于偏微分方程的maldi质谱峰检测方法
GB201902780D0 (en) 2019-03-01 2019-04-17 Micromass Ltd Self-calibration of arbitary high resolution mass spectrum
JP7018422B2 (ja) * 2019-12-06 2022-02-10 日本電子株式会社 マススペクトル処理装置及び方法
US11721534B2 (en) * 2020-07-10 2023-08-08 Bruker Daltonik Gmbh Peak width estimation in mass spectra
CN117751194A (zh) * 2021-07-19 2024-03-22 株式会社岛津制作所 同位素分布数据生成方法

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050086017A1 (en) * 2003-10-20 2005-04-21 Yongdong Wang Methods for operating mass spectrometry (MS) instrument systems

Family Cites Families (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5532122A (en) * 1993-10-12 1996-07-02 Biotraces, Inc. Quantitation of gamma and x-ray emitting isotopes
GB9801565D0 (en) * 1998-01-23 1998-03-25 Micromass Ltd Method and apparatus for the correction of mass errors in time-of-flight mass spectrometry
DE19803309C1 (de) * 1998-01-29 1999-10-07 Bruker Daltonik Gmbh Massenspektrometrisches Verfahren zur genauen Massenbestimmung unbekannter Ionen
SE0000754D0 (sv) * 2000-03-07 2000-03-07 Amersham Pharm Biotech Ab Mass spectral peak identification
US7577538B2 (en) * 2003-04-28 2009-08-18 Cerno Bioscience Llc Computational method and system for mass spectral analysis
US7529629B2 (en) * 2003-04-28 2009-05-05 Cerno Bioscience Llc Computational methods and systems for multidimensional analysis
US20050255606A1 (en) * 2004-05-13 2005-11-17 Biospect, Inc., A California Corporation Methods for accurate component intensity extraction from separations-mass spectrometry data
GB2404194A (en) * 2003-07-21 2005-01-26 Amersham Biosciences Ab Automated chromatography/mass spectrometry analysis
JP5227026B2 (ja) * 2004-10-28 2013-07-03 セルノ・バイオサイエンス・エルエルシー 定性的なおよび定量的な質量スペクトル分析
US7348553B2 (en) * 2004-10-28 2008-03-25 Cerno Bioscience Llc Aspects of mass spectral calibration
US20060255258A1 (en) * 2005-04-11 2006-11-16 Yongdong Wang Chromatographic and mass spectral date analysis
US7451052B2 (en) * 2005-05-29 2008-11-11 Cerno Bioscience Llc Application of comprehensive calibration to mass spectral peak analysis and molecular screening
US8691774B2 (en) * 2005-07-11 2014-04-08 Glykos Finland Oy Carbohydrate profile compositions from human cells and methods for analysis and modification thereof
US8759005B2 (en) * 2005-07-11 2014-06-24 Glykos Finland Oy Tissue carbohydrate compositions and analysis thereof
FI20055417A0 (fi) * 2005-07-20 2005-07-20 Glykos Finland Oy Syöpäpesifiset glykaanit ja niiden käyttö
US7781729B2 (en) * 2006-05-26 2010-08-24 Cerno Bioscience Llc Analyzing mass spectral data
US20090162938A1 (en) * 2005-11-08 2009-06-25 Suomen Punainen Risti,Veripalvelu Novel Carbohydrate Profile Compositions From Human Cells and Methods for Analysis and Modification Thereof
WO2007059117A2 (en) * 2005-11-10 2007-05-24 Rosetta Inpharmatics Llc Discover biological features using composite images
US8084734B2 (en) * 2006-05-26 2011-12-27 The George Washington University Laser desorption ionization and peptide sequencing on laser induced silicon microcolumn arrays

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050086017A1 (en) * 2003-10-20 2005-04-21 Yongdong Wang Methods for operating mass spectrometry (MS) instrument systems

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080001079A1 (en) * 2006-05-26 2008-01-03 Yongdong Wang Analyzing mass spectral data
US7781729B2 (en) * 2006-05-26 2010-08-24 Cerno Bioscience Llc Analyzing mass spectral data
US10943775B2 (en) * 2016-09-02 2021-03-09 Board Of Regents, The University Of Texas System Collection probe and methods for the use thereof
US11239065B2 (en) 2016-09-02 2022-02-01 Board Of Regents, The University Of Texas System Collection probe and methods for the use thereof
US11756778B2 (en) 2016-09-02 2023-09-12 Board Of Regents, The University Of Texas System Collection probe and methods for the use thereof
US11737671B2 (en) 2017-11-27 2023-08-29 Board Of Regents, The University Of Texas System Minimally invasive collection probe and methods for the use thereof
WO2019118900A1 (en) * 2017-12-14 2019-06-20 California Institute Of Technology Systems and methods for predicting and interpreting comprehensive molecular isotopic structures and uses thereof
CN112771375A (zh) * 2018-06-22 2021-05-07 伊罗亚科技有限公司 校正离子源效率低下的方法使得样品间归一化成为可能
CN111325121A (zh) * 2020-02-10 2020-06-23 浙江迪谱诊断技术有限公司 一种核酸质谱数值处理方法

Also Published As

Publication number Publication date
EP2160570A4 (en) 2012-12-05
US20100171032A1 (en) 2010-07-08
JP2010529457A (ja) 2010-08-26
CA2689417C (en) 2017-07-11
EP2160570A1 (en) 2010-03-10
JP5704917B2 (ja) 2015-04-22
CA2689417A1 (en) 2008-12-11
WO2008151153A1 (en) 2008-12-11
US8803080B2 (en) 2014-08-12

Similar Documents

Publication Publication Date Title
US20080302957A1 (en) Identifying ions from mass spectral data
JP4686450B2 (ja) 質量スペクトル分析の計算方法およびシステム
US7904253B2 (en) Determination of chemical composition and isotope distribution with mass spectrometry
US8927925B2 (en) Interactive method for identifying ions from mass spectral data
JP5027511B2 (ja) 質量分析（ｍｓ）およびその他の計測器システムを較正し、ｍｓおよびその他のデータを処理するための方法
Castro-Perez Current and future trends in the application of HPLC-MS to metabolite-identification studies
JP5393449B2 (ja) 質量スペクトルデータの解析
JP7377805B2 (ja) 確実で自動の質量スペクトル分析
JP2008536147A (ja) クロマトグラフィおよび質量スペクトルのデータ分析
US20090210167A1 (en) Computational methods and systems for multidimensional analysis
Tebani et al. Optimization of a liquid chromatography ion mobility-mass spectrometry method for untargeted metabolomics using experimental design and multivariate data analysis
CN102798684A (zh) 一种基于保留时间锁定-气相色谱-四极杆质谱选择性离子扫描的化学轮廓分析方法
Yu et al. A chemometric-assisted method based on gas chromatography–mass spectrometry for metabolic profiling analysis
JP4686451B2 (ja) 多次元分析の計算方法およびシステム
US20200232956A1 (en) Accurate mass spectral library for analysis
EP3523818B1 (en) System and method for real-time isotope identification
US11694884B2 (en) Mass spectral analysis of large molecules
Bielow et al. Bioinformatics for qualitative and quantitative proteomics
Sarycheva et al. Robust Simulation Of Imaging Mass Spectrometry Data.
JP2024526079A (ja) 質量スペクトル中の分子種を同定するための方法及び装置
Lange Analysis of mass spectrometric data: peak picking and map alignment
WO2023076602A1 (en) Accurate spectral library search

Legal Events

Date Code Title Description
AS Assignment

Owner name: CERNO BIOSCIENCE LLC, CONNECTICUT

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:WANG, YONGDONG;GU, MING;REEL/FRAME:023610/0016

Effective date: 20080613

STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION