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WO2000029987A1 - Procedes servant a identifier et a classifier des organismes par spectrometrie de masse et recherche dans une base de donnees - Google Patents

Procedes servant a identifier et a classifier des organismes par spectrometrie de masse et recherche dans une base de donnees Download PDF

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Publication number
WO2000029987A1
WO2000029987A1 PCT/US1999/027191 US9927191W WO0029987A1 WO 2000029987 A1 WO2000029987 A1 WO 2000029987A1 US 9927191 W US9927191 W US 9927191W WO 0029987 A1 WO0029987 A1 WO 0029987A1
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mass
protein
proteins
database
sample
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PCT/US1999/027191
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English (en)
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Plamen A. Demirev
Catherine Fenseleau
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University Of Maryland
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Priority to US09/856,044 priority Critical patent/US7020559B1/en
Priority to AU19150/00A priority patent/AU1915000A/en
Publication of WO2000029987A1 publication Critical patent/WO2000029987A1/fr

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • G16B30/10—Sequence alignment; Homology search
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids

Definitions

  • Fig. 1 Molecular mass distribution (in bins of 1 kDa) of proteins deposited in the SwissPROT/TrEMBL sequence database: a) all prokaryotic proteins, and b) all proteins from B.subtilis.
  • Fig. 2 Positive ion MALDI spectra from: a) B.subtilis (8 hours growth time), matrix - SA; and b) E.coli (32 hours growth time), matrix - CHCA.
  • Fig. 3 Positive ion MALDI spectra from: a) E.coli (32 hours growth time), matrix - MCA:SA mixture; and b) E.coli (8 hours growth time), matrix - CHCA.
  • Fig. 4 Number of proteins combined from B.subtilis and E.coli with masses within a predetermined mass window (in ppm) as a function of molecular mass.
  • Fig. 5 Positive ion MALDI spectrum from a mixture of B.subtilis and E.coli, matrix - SA.
  • Fig. 6 An example of a flow chart for microroganism and cell identification by mass spectrometry and database searching.
  • the present invention relates to compositions of matter, instruments, processes (e.g., as carried using computer software and/or hardware), and methods, for identifying, classifying, and or characterizing biological materials by measuring the molecular weights of protein constituents in such materials and using the molecular information to deduce the organismic source of the biological materials.
  • biological materials comprising proteins can be subjected to mass spectrometry, or other suitable means for determining mass, in order to determine the molecular weights of the protein constituents.
  • the resulting molecular weight information of the protein constituents can then be used to query databases which contain, among other information, lists of protein molecular weight information and the identity of the organism source from which the information was derived.
  • the present invention presents a method for rapid identification, classification, and or characterization of biological materials, such as microorganisms, organisms, organs, tissues, cells, subcellular materials, and the like, which exploits the wealth of information contained in genome and protein sequence databases.
  • biological materials such as microorganisms, organisms, organs, tissues, cells, subcellular materials, and the like.
  • the massive efforts to sequence the human genome has brought about a rapid increase in the speed with which DNA sequences from all species are being accumulated in publicly available computer databases.
  • any instrument, method, process, etc. can be utilized to determine the molecular weight of proteins in a sample.
  • a preferred method of obtaining molecular weight is by mass spectrometry, where protein molecules in a sample are ionized and then the resultant mass and charge of the protein ions are detected and determined.
  • any suitable instrument, method, process, etc. for carrying out mass spectroscopy can be utilized.
  • mass spectrometry to analyze proteins, it is preferred that the protein be converted to a gas-ion phase.
  • Various methods of protein ionization are useful, including, e.g., fast ion bombardment (FAB), plasma desorption, laser desorption, thermal desorption, preferably, electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI).
  • FAB fast ion bombardment
  • ESI electrospray ionization
  • MALDI matrix-assisted laser desorption ionization
  • Many different mass analyzers are available for peptide and protein analysis, including, but not limited to, Time-of-Flight (TOF), ion trap
  • ITMS Fourier transform ion cyclotron
  • FTMS Fourier transform ion cyclotron
  • quadrupole ion trap and sector (electric and/or magnetic) spectrometers. See, e.g., U.S. Pat. No. 5,572,025 for an ion- trap MS.
  • Mass analyzers can be used alone, or in combination to form tandem mass spectrometers. In the latter case, a first mass analyzer can be use to separate the protein ions (precursor ion) from each other and determine the molecular weights of the various protein constituents in the sample. A second mass analyzer can be used to analyze the separated constituents, e.g., by fragmenting the precursor ions into product ions. Any desired combination of mass analyzers can be used, including, e.g., triple quadrupoles, tandem time-of-flights, ion traps, and/or combinations thereof. Different kinds of detectors can be used to detect the protein ions.
  • destructive detectors can be utilized, such as ion electron multipliers or cryogenic detectors (e.g., U.S. Pat. No. 5,640,010).
  • non-destructive detectors can be used, such as an ion trap which is utilized in an ion current pick-up devices which are utilized in quadrupole ion trap mass analyzers or FTMS.
  • Any source of proteins can be used in accordance with the present invention, including whole organisms, such as multicellular and unicellular organisms, organs, tissues, cells, subcellular structures, and mixtures thereof.
  • microorganisms can be utilized, e.g., archeabacteria, bacteria, chlamydiae, rickettsia, viruses, mycoplasma, molds, yeasts, protozoa, algae, prions, etc.
  • Cells, microorganisms, etc. can be genetically-engineered, altered, modified, etc.
  • Proteins can be extracted from intact or treated materials. Any substrate comprising a biological material can be used. For instance, it may be desirable to characterize organisms found on surfaces, in food, in biological fluids, such as saliva, urine, fecal matter, blood, lymph, or plasma, on materials used to wipe surfaces suspected of containing organisms, in hair, objects handled or contacted by organisms, etc.
  • sample preparation methods can be utilized including, dried droplet (Karas and Hillenkamp, Anal. Chem., 60:2299-2301, 1988), vacuum-drying (Winberger et al, In Proceedings of the 41st ASMS Conference on Mass Spectrometry and Allied Topics, San Francisco, May 31 -June 4, 1993, pp. 775a-b), crush crystals (Xiang et al, Rapid
  • samples of microorganisms can be lyophilized, extracted into a solution, such as a 70:30 solution of CH 3 CN:0.1% trifluoroacetic acid, and then embedded in the matrix.
  • a solution such as a 70:30 solution of CH 3 CN:0.1% trifluoroacetic acid
  • Various matrices can be used, e.g., sinapinic acid, 2,5-dihydroxybenzoic acid, alpha-cyano-4-hydroxycinaminnic acid.
  • a sample can be processed in various ways prior to addition to the matrix. For instance, the sample can be extracted, subjected to corona discharge, chromatography, such as HPLC, etc., e.g., to remove particular unwanted constituents (such as lipids, small molecules, high molecular weight constituents) before mass spectrometry.
  • MALDI-TOF can detect proteins at the attamole level over a wide range of molecular weights. Masses can be determined, e.g., as low as 1000, and as high as a hundred-thousand daltons. Any range of molecular weights can be used in accordance with the present invention, e.g., about 4000-20,000. Masses accurate to about 50 ppm or better will be most reliable in the general case.
  • a specific peak matches more than one different protein in the searched databases. This can happen when different proteins share the same, or similar, molecular weights.
  • a search of a database in such a case might reveal more than one protein which corresponds to the measured molecular weight of a protein in the sample.
  • the peak protein can be separated from the mixture and subjected to further physical characterization.
  • Separation can be accomplished by any suitable method, e.g., conventional techniques involving, e.g, by cell lysis, extraction, and two-dimensional gel chromatography, capillary electrophoresis, or high performance liquid chromatography
  • Usefiil information includes, amino acid composition, amino acid sequence, proteolytic and enzymatic cleavage patterns, isoelectric point, hydrophobicity, and other physical characteristics.
  • Another scenario where additional information on a protein in spectrum may be warranted is where such protein has not matched any of the proteins listed in the database. Thus, such information can be useful to increase the specificity of the approach.
  • proteomics e.g. for rapid identification of proteins present in a mixture in picomolar amounts
  • MS-based procedures for identity assignment of individual proteins.
  • These methods include, but are not limited to, chemical/enzymatic digestion of material (obtained from a single spot in a two- dimensional gel electropherogram, or by other suitable chromatographic technique) and mass spectral determination of the molecular masses of the protein and resulting peptides (peptide mapping). Making use of already available information in protein sequence databases, a comparison can made between proteolytic peptide mass patterns generated "in silico," and experimentally-observed peptide masses.
  • a "hit-list” can be compiled, ranking candidate proteins in the database, based on (among other criteria) number of matches between the proteolytic fragments.
  • Several Web sites are accessible that provide software for protein identification on-line, based on peptide mapping and sequence database search strategies.
  • Data collected from a mass spectrometer typically comprises the intensity and mass to charge ratio for each detected event.
  • Spectral data can be recorded in any suitable form, including, e.g., in graphical, numerical, or electronic formats, either in digital or analog form.
  • Spectra is preferably recorded in a storage medium, including, e.g., magnetic, such as floppy disk, tape, or hard disk; optical, such as CD-ROM or laserdisc; or, ROM-CHIPS.
  • the mass spectrum of a given sample typically provides information on protein intensity, mass to charge ratio, and molecular weight.
  • the molecular weights of proteins in the sample are used as a matching criterion to query a database.
  • the molecular weights are calculated conventionally, e.g., by subtracting the mass of the ionizing proton for singly-charged protonated molecular ions, by multiplying the measured mass-over-charge-ratio by the number of charges for mutliuply-charged ions and subtracting the number of ionizing protons.
  • Various databases are useful in accordance with the present invention. Useful databases include, databases which contain genomic sequences, expressed gene sequences, and/or expressed protein sequences.
  • Preferred databases contain nucleotide sequence-derived molecular masses of proteins present in a known organism, organ, tissue, or cell-type. There are a number of algorithms to identify open reading frames (ORF) and convert nucleotide sequences into protein sequence and molecular weight information.
  • ORF open reading frames
  • Several publicly accessible databases are available, including, SwissPROT/TrEMBL database which contains substantial entries for a variety of organisms, including, B. subtilis and E. coli.
  • TIGR Microbial Database http://www.tigr.org/tdb/mdb/mdb.html
  • VanBogelen et al. Escherichia coli and Salmonella: Cellular and Molecular Biology, ASM Press
  • Information contained in the databases includes, e.g., gene name, protein name, E.C. number, category of function, Swiss-Prot accession code, sequence code for Genbank, Kohara phage location, genetic map location, direction of transcription on the chromosome, predicted molecular weight and isoelectric point from DNA sequence, etc.
  • One or more databases can be searched using any suitable search algorithm.
  • search algorithm for example, the SwissProt/TrEMBL database ("Expasy,” Swiss Bioinformatics Institute) using the Sequence Retrieval System (SRSWWW) module.
  • SRSWWW Sequence Retrieval System
  • any search strategy can be utilized in accordance with the present invention.
  • a mass spectrometer is equipped with commercial software that identifies peaks above a certain threshold level, calculates mass, charge, and intensity of detected ions. Correlating molecular weight with a given output peak can be accomplished directly from the spectral data, i.e., where the charge on an ion is one and the molecular weight is therefore equal to the numerator value minus the mass of the ionizing proton.
  • protein ions can be complexed with various counter-ions and adducts, such as Na ⁇ , and K + . In such a case, it would be expected that a given protein ion would exhibit multiple peaks, such as a triplet, representing different ionic states (or species) of the same protein.
  • post- translation processing may have to be considered.
  • processing events which modify protein structure in a cell, including, proteolytic processing, removal of N-terminal methionine, acetylation, methylation, glycosylation, etc.
  • a database can be queried for a range of proteins which match the molecular mass of the unknown.
  • the range window can be determined by the accuracy of the instrument, the method by which the sample was prepared, etc. Based on the number of hits (where a hit is match) in the spectrum, the unknown is identified or classified.
  • a preferred method of the present invention concerns identifying one or more unknown microorganisms in a sample, comprising: searching a sequence database for a plurality of different proteins that have the molecular weights of proteins in a mass spectrum of a sample, wherein said sample comprises a plurality of proteins from one or more unknown microorganisms, whereby said one or more unknown microorganisms are identified.
  • Identifying is meant in the general sense. For example, when an unknown microorganism is utilized in the aforementioned method, an objective is to determine the character of the unknown. This can mean finding out the particular taxonomic group(s) to which the microorganism belongs, such as its kingdom, phylum, class, order, family, genus, species, variety, and or strain. By determining that the sample is derived from a bacteria, the sample is thus classified as a bacteria. Identification in this sense can be as precise as the materials and methods allow. For some purposes, it may be enough to identify a sample as derived from a set of possible groups; however, other purposes may demand more precision.
  • a database is searched for proteins which have the molecular weights of protein constituents in the sample.
  • a database is a collection of organized information in a form which can be searched and retrieved by a computer, or other electronic processing means.
  • the searching can be accomplished usually any suitable, effective, search algorithm that can determine the presence of entries in the database which have the same, or within a specified range, molecular weight of proteins in the mass spectrum of the unknown sample.
  • the database as mentioned earlier, can comprise genomic sequences, expressed genes, protein sequences, protein molecular weights, etc.
  • the database contains nucleotide information
  • this information can be translated into protein data before the searching step, e.g., by identifying an ORF, proteolytic and cleavage sites, glycosylation sites, methylation sites, and other processing which can influence the mass of a protein.
  • the searching step can be characterized as searching for proteins which are "predicted" to have molecular weights.
  • a search in accordance with the present invention means, e.g., that a database is queried or probed for the presence of a data which matches or corresponds to the measured data, such as the measured data obtained from a mass spectrum.
  • the database is search for a plurality of different proteins, i.e., more than one, preferably more than 5, etc.
  • identification reliability will depend on a number of factors, including the number of peaks in a matched spectrum matched to proteins in a database, the number and accuracy of proteins predicted from the genome sequence in the mass range under study, etc.
  • different it is meant that the proteins arise from different genes, such as a gene coding for a protease and a gene coding for an amylase.
  • a search strategy can use the information generated by MS, or any other method, to search a database.
  • a simple search and find strategy can be used where the database is queried for proteins which match the molecular weight of the inputted data.
  • Fig. 6 is an example of a process of identifying an unknown organism, cell, or other biological material.
  • One or more of the steps depicted in the flow chart can be used to identify an organism in accordance with the present invention.
  • a mass spectrum of a sample comprising proteins from an unknown organism has already been generated using MALDI/TOF spectrometry.
  • the output from the mass spectrometer is represented as a series of m z values, where m is the mass of a protein plus the mass of a proton or other charging species, and z is the net number of charges carried by the ion and is used as the initial input 1.
  • the input masses are processed 2, e.g., by subtracting one dalton to correct for the proton added to the protein when it is ionized through gas- phase proton transfer reaction of MALDI.
  • the input data can additionally processed by determined an average molecular weight or a monoisotopic mass.
  • a protein will typically be represented in a mass spectrum by more than one peak because of the presence in it of more than one isotope. Carbon, for instance, occurs in nature as C-12 or C-13 in a ratio of about 100: 1. Therefore, if a compound contains a single carbon, it would be expected that 99% of it would be C-12 and 1% of it would be C-13. The mass spectrum of such compound would therefore have at least two peaks, each corresponding to a different carbon isotope.
  • a mass spectrum of such a compound would contain multiple peaks for each polyisotopic molecule.
  • a compound containing a plurality of atoms represented by more than one isotope will have a complex pattern of spectral peaks.
  • Such complex spectral information can be processed in a number of ways. A average mass can be calculated, e.g., using the empirical spectral information. Alternatively, a monisotopic mass can be calculated where a mass is derived where the mass of only one isotope of each atom is represented in the molecule.
  • a mass window is set 3 to define a mass range in which matches in the database will be scored as hits.
  • the mass window for a particular query can be set based on various criteria.
  • One consideration is the accuracy of the instrument. For instance, if the instrument can only measure values within three daltons, then the mass window could be for ⁇ 3 Da.
  • Other considerations include, post- translational processing.
  • the accuracy of the instrument can be determined routinely, e.g., using known standards and calibrating the instrument using an external and internal standard.
  • the processed data resulting from 2 is used as input data to initiate a search 4 of a database containing protein masses.
  • the database comprises nucleotide sequence information which has been analyzed to predict the occurrence of open reading frames (ORF) and the calculated molecular masses of such ORFs.
  • ORF open reading frames
  • various public and private databases are available that contain calculated protein mass information, or which can be mined by available software to derive such information.
  • the search mode queries the database for proteins having molecular masses which match up with the molecular masses in the mass spectrum input data 2. For each peak in the input data 2, the database is queried and a list is generated of putative database proteins which match it.
  • a match is identified in the database if it possesses the same mass as the peak, or if it is within the range indicated in the mass window 3.
  • a first list 6 can be generated which reflects the masses and organismic sources for each match. For example, each mass spectral peak of 2 can be associated with a family of proteins, representing proteins of the same molecular mass but from different organisms and proteins within the mass range set in 3.
  • the data in 6 can optionally be refined 7 by inputting additional data 8, e.g., from fragmented precursor ions of 1 and collecting data of peptide mass, sequence tag information from mass spectra, or other types of downstream information on the constituent proteins.
  • additional data e.g., from fragmented precursor ions of 1 and collecting data of peptide mass, sequence tag information from mass spectra, or other types of downstream information on the constituent proteins.
  • data, or orthogonal information can, e.g., increase certainty that the identification is correct and/or reduce the number of positive hits identified in a search.
  • a search identifies X possible proteins in the database which match the query by being within the mass window set in 3
  • a step 8 can be used to reduce the number of possible hits.
  • sequence information or proteolytic information can be used to determine which specific hit, in the set of hits identified for the specified mass range, corresponds to the data point of interest in the mass spectrum.
  • amino sequence or composition information obtained from a peak of interest can be used to search the set of hits identified as matching the peak of interest to ascertain which hit contains the sequence information.
  • Sequence can information can be highly specific, eliminating all other peaks having the same molecular weight from the list generated in 7.
  • Amino acid composition information can also be used a refining tool, although it may be less specific. Any supplemental information on the physical characteristics of a protein can be used to confirm and/or reduce the number of hits identified in a search, including, sequence information as mentioned, cleavage patterns
  • the data from 6 or 7 can then be scored to generate an output list 10 which lists the possible organisms sources of the mass spectrum.
  • the identified organismic sources can be ranked based on a number of criteria, including, but not limited to, total number of proteins identified as matching an organismic source, orthogonal information obtained in 8, etc. Table 1, for instance shows that B. subtilis contains 12/15 or 80% matching peaks and E. coli contains 6/15 or 40% matching peaks, If percent match is the sole criteria, B. subtilis would be ranked above E. coli.
  • the proteins which are unidentified e.g., the three proteins listed in
  • Table 1 for B. subtilis in the list can be subjected to further analysis in an interation step 10.
  • One reason that a matching protein is not identified in the database may be that the protein is subjected to post-translational modifications and therefore does not have the molecular weight predicted by ORF analysis.
  • An advantage of the present invention is that it can be independent of the specific ionization technique and mass analyzer utilized, alleviating the requirement for rigorous reproducibility, crucial in currently used fingerprint-based approaches.
  • the approach introduced here is independent of relative signal intensities in the mass spectrum. It does not even require that the same set of proteins be expressed and/or detected in each analysis of the same organism, only that a set is characteristic so that it can be associated with a microorganism source.
  • sample preparation, ionization and mass analysis for obtaining mass spectra are not restrictive for the described approach, which also has a potential to be used for identification of cells from individual tissues.
  • the present invention can be used in variety of different ways and settings and has useful applications in the lab, field, and environmental testing. For example, it can be used in human and veterinary medicine to diagnose normal and pathological conditions from biological materials, such as blood, plasma, urine, sperm, fecal matter, and saliva.
  • biological materials such as blood, plasma, urine, sperm, fecal matter, and saliva.
  • the present invention is also useful in research and industry. Food samples can be obtained from food materials suspected of contamination.
  • SA Sinapinic acid
  • CHCA «- cyano-4-hydroxycinnamic acid
  • MCA 4-methoxycinnamic acid
  • MALDI mass spectrometry a solution of bovine insulin and bovine ubiquitin was added to the E.coli sample/matrix mixture on the sample slide in order to increase the accuracy of mass determination.
  • an internal mass calibration standard a solution of bovine insulin and bovine ubiquitin
  • B.subtilis external calibration of the instrument using a mixture of proteins (bovineinsulin, bovine ubiquitin and horse heart cytochrome C) was performed prior o running the samples. All proteins were obtained from Sigma Chemical Co. (St. Louis, MO).
  • Positive ion mass spectra (typically from 50 single laser shots rastered uniformily across the sample spot) were recorded in linear mode at 20 kV accelerating voltage and a delay of 0.3 ⁇ s.
  • the estimated N 2 laser fluence was around 10 mJ-cm "2 .
  • the MALDI spectra (Fig. 2) of B.subtilis and E.coli contain multiple peaks between 4 and 10 kDa with a signal to noise ratio better than 3.

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Abstract

Procédé d'identification rapide de matériaux biologiques, qui exploite la richesse des informations contenues dans des bases de données (5) de séquences de protéines et du génome. Dans un mode de réalisation préféré, ce procédé utilise les masses d'un ensemble d'ions par spectrométrie de masse de MALDI TOF de cellules intactes ou traitées (1). On effectue une corrélation subséquente (4) de chaque ion de l'ensemble avec une protéine, ainsi qu'avec une source organismique de la protéine, par recherche dans une base de données comprenant des poids moléculaires (9) de protéines.
PCT/US1999/027191 1998-11-17 1999-11-17 Procedes servant a identifier et a classifier des organismes par spectrometrie de masse et recherche dans une base de donnees WO2000029987A1 (fr)

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DE10038694A1 (de) * 2000-07-28 2002-02-14 Anagnostec Ges Fuer Analytisch Verfahren zur Identifizierung von Mikroorganismen mittels MALDI-TOF-MS
WO2002027329A3 (fr) * 2000-09-25 2003-08-07 Eastern Virginia Med School Biomarqueurs du carcinome transitionnel de la vessie
WO2003074727A1 (fr) * 2002-03-01 2003-09-12 De Montfort University Identification rapide de levures
US6680203B2 (en) 2000-07-10 2004-01-20 Esperion Therapeutics, Inc. Fourier transform mass spectrometry of complex biological samples
EP1437673A1 (fr) 2003-01-07 2004-07-14 AnagnosTec, Gesellschaft für Analytische Biochemie und Diagnostik mbH Méthode d'identification de microorganismes par la spectrométrie de masse
US6800449B1 (en) 2001-07-13 2004-10-05 Syngenta Participations Ag High throughput functional proteomics
US7061605B2 (en) 2000-01-07 2006-06-13 Transform Pharmaceuticals, Inc. Apparatus and method for high-throughput preparation and spectroscopic classification and characterization of compositions
US7108970B2 (en) 2000-01-07 2006-09-19 Transform Pharmaceuticals, Inc. Rapid identification of conditions, compounds, or compositions that inhibit, prevent, induce, modify, or reverse transitions of physical state
US7133864B2 (en) 2001-08-23 2006-11-07 Syngenta Participations Ag System and method for accessing biological data
CN100364355C (zh) * 2004-07-29 2008-01-23 大唐移动通信设备有限公司 利用实测数据平铺获得小区覆盖的方法
US7811772B2 (en) 2005-01-06 2010-10-12 Eastern Virginia Medical School Apolipoprotein A-II isoform as a biomarker for prostate cancer
WO2011123479A1 (fr) * 2010-03-29 2011-10-06 Academia Sinica Mesure quantitative de l'endocytose de nano/microparticules par spectrométrie de masse cellulaire
WO2012044170A1 (fr) * 2010-10-01 2012-04-05 Nederlandse Organisatie Voor Toegepast-Natuurwetenschappelijk Onderzoek Tno Nouvelle méthode de classification pour données spectrales
CN107782886A (zh) * 2011-04-21 2018-03-09 生物梅里埃公司 使用质谱检测至少一种头孢菌素抗性机制的方法
CN111257404A (zh) * 2016-01-14 2020-06-09 萨默费尼根有限公司 用于蛋白质或多肽的混合物的从上到下多路复用质谱分析的方法

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