【分类专业数据库荟萃】 蛋白质相互作用数据库 <原创>
推荐这个帖子发布于 22 年零 44 天前，其中的信息可能已发生改变或有所发展。
－－
即将推出几个分类专业数据库的介绍，这些都是今半年中在nature,science等杂志中频频引用的专业数据库，希望大家能根据所需很好的利用！我们还会跟踪，及时update!
[分类专业数据库介绍 ]蛋白质相互作用数据库分类分类
【原创文章||转载请注明来自丁香园©】
暂时为英文版，中文版编译中ing......
【BIND】 - Biomolecular Interaction Network Database (*)(*)(*)(*)(*)
[Introduction]
We have designed and implemented a new database encompassing the growing network of protein and other biomolecular interactions, called BIND (Biomolecular Interaction Network Database).
This database will span the complexity of interaction information gathered through experimental studies of biomolecular interactions. Interaction information will come from the literature, submitters and other databases.
BIND contains interaction, molecular complex and pathway records.
[Link]http://www.bind.ca
--------------------------------------------------------------------------------
【DIP】 - Database of Interacting Proteins (*)(*)(*)(*)(*)
[Introduction]
DIP (Database of Interacting Proteins) is a database of protein pairs that are known to interact with each other. By interact we mean two amino acid chains that bind to each other for a function. The idea is to provide well defined links between proteins that interact. The database is publicly available on the web and is intended to aid those studying protein-protein interactions, signaling pathways, multiple interactions and complex systems.
[Link]http://dip.doe-mbi.ucla.edu/
--------------------------------------------------------------------------------
【PIM】 - Hybrigenics (*)(*)(*)
[Introduction]
Protein Interaction Maps: PIMs. for whole microbial pathogen genomes or selected cDNA libraries. First PIMs. available:
Helicobacter pylori (example below)
Hepatitis C Virus
Saccharomyces cerevisiae
[Link]http://www.hybrigenics.fr/
--------------------------------------------------------------------------------
【PathCalling Yeast Interaction Database 】(*)(*)(*)
[Introduction]
PathCalling is CuraGen's validated, industrial scale proteomic technology designed to functionally analyze important disease related or drug response proteins. PathCalling is an automated and fully operational technology powered by GeneScape., CuraGen's Internet-based operating portal. PathCalling enables scientists to:
Identify protein-protein interactions on a genome-wide scale - Knowledge of interacting proteins provides insight into the function of important genes, elucidates relevant pathways, and facilitates the identification of potential drug targets for use in developing novel therapeutics
Rapidly interpret protein-protein interactions - Powerful bioinformatics software enables comparative cross-species genomic analysis, accelerating functional assignment and drug target discovery
Traverse up and down pathways - Expanding biological pathways involved in disease and drug response increases knowledge of the system, and enables scientists to identify both genes and proteins not previously associated with disease or drug response
[Link]http://portal.curagen.com/extpc/com.curagen.portal.servlet.Yeast
--------------------------------------------------------------------------------
【MINT】 - a Molecular Interactions Database (*)(*)(*)(*)(*)
[Introduction]
MINT is a database designed to store functional interactions between biological molecules (proteins, RNA, DNA). Beyond cataloguing the formation of binary complexes, MINT was conceived to store other type of functional interactions namely enzymatic modifications of one of the partners. Presently MINT focuses on experimentally verified protein-protein interactions. Both direct and indirect relationships are considered.
MINT consists of entries extracted from the scientific literature by expert curators assisted by 'MINT Assistant' a software that targets abstracts containing interaction information and prsents them to the curator in a user friendly format.
The interaction data can be easily extracted and viewed graphically by 'MINT Viewer'.
[Link]http://cbm.bio.uniroma2.it/mint/
--------------------------------------------------------------------------------
【GRID】 - The General Repository for Interaction Datasets (*)(*)(*)(*)(*)
[Introduction]
The General Repository for Interaction Datasets (GRID) is a database of genetic and physical interactions developed in The Tyers Group at the Samuel Lunenfeld Research Institute at Mount Sinai Hospital. It contains interaction data from many sources, including several genome/proteome-wide studies, the MIPS database, and BIND.
[Link]http://biodata.mshri.on.ca/grid/servlet/Index
--------------------------------------------------------------------------------
【InterPreTS】 - protein interaction prediction through tertiary structure (*)(*)(*)(*)
[Introduction]
InterPreTS (Interaction Prediction through Tertiary Structure) is a web-based tool for predicting protein-protein interactions. Given a pair of query sequences, it first searches for homologues in a database of interacting domains (DBID) of known three-dimensional complex structures. Pairs of sequences homologous to a known interacting pair are scored for how well they preserve the atomic contacts at the interaction interface.
[Link]http://www.russell.embl.de/interprets/
--------------------------------------------------------------------------------
【STRING】 - predicted functional associations among genes/proteins (*)(*)(*)(*)
[Introduction]
STRING is a database of predicted functional associations among genes/proteins.
Genes of similar function tend to be maintained in close neighborhood, tend to be present or absent together, i.e. to have the same phylogenetic occurrence, and can sometimes be found fused into a single gene encoding a combined polypeptide. STRING integrates this information from as many genomes as possible to predict functional links between proteins.
[Link]http://www.bork.embl-heidelberg.de/STRING/
--------------------------------------------------------------------------------
【BID】(*)(*)(*)
[Introduction]
An overflow of information on the characterization of protein-protein interactions at the amino-acid level is continuing to develop with the goal of better understanding protein interfaces. For this reason it is necessary to acquire a protein-protein interaction database in which an enormous number of interactions can be easily accessed.
[Link]http://tsailab.tamu.edu/BID/
--------------------------------------------------------------------------------
【PPID】 (*)(*)(*)
[Introduction]
The Protein-Protein Interaction Database was originally a single-person's attempt to integrate a gamut of biological/bibliographical/molecular data and build a framework which might help understanding how cells orchestrate their protein content in order to become what they are: machines with a purpose. This is based on the simple paradigm that functionality like signal cascades are held together in a close space, thereby allowing specific events to occur without the necessity of passive diffusion and random events. The PPID database arose from the need to interpret Proteomic datasets, which were generated analysing the NMDA-receptor complex (see H. Husi, M. A. Ward, J. S. Choudhary, W. P. Blackstock and S. G. Grant (2000). Proteomic analysis of NMDA receptor-adhesion protein signaling complexes. Nat Neurosci 3, 661-669.). To study these clusters of proteins requires unavoidably the handling of large datasets, which PPID is generally aimed and tailored for. This database is unifying molecular entries across three species, namely human, rat and mouse and is is footed on sequence databases such as SwissProt, EMBL, TrEMBL (translated EMBL sequences) and Unigene and the literature database PubMed. A typical entry in PPID holds up to three general entries for the three species, all protein and gene accession numbers associated with them (assembled from Blast2 searches of the databases) and the OMIM entry as maintained by Johns Hopkins University. Furthermore protein sequence information is also included, together with known and novel splice-variants of each molecule as found by ClustalW sequence alignments. Entry points also include protein-binding information together with the literature reference. The whole database is curated manually to insure accuracy and quality. Querying the database will be possible by online browsing and batch-submission for large datasets holding accession number information, as can be generated using software like Mascot for mass-spectrometry. Cluster-analysis of the submitted datasets in the form of a graphical output will be developed as well as an easy-to-use web-interface.
An interface is currently being built in collaboration with the Department of Informatics (T. Theodosiou and D. Armstrong) and will be deployed soon
[Link]http://www.anc.ed.ac.uk/mscs/PPID/
----------------------------------------------------------------------------------------------
【C. elegans Protein Interactome 】
[Introduction]
This website is now unavailable! --June 13, 2003 Biozy
------------------------------------------------------------------------------------------------
【SPID】Subtilis Protein interaction Database (*)(*)(*)(*)
[Introduction]
To date, the Database Contains 95 Interactions between 68 Proteins.
[Link]http://www-mig.jouy.inra.fr/bdsi/SPiD/
-------------------------------------------------------------------------------------------------
【Mouse Protein-Protein interactions 】Just some datasets (*)(*)(*)
[Introduction]
Just some datasets about mouse protein-protein interaction
http://genome.gsc.riken.go.jp/ppi/
-------------------------------------------------------------------------------------------------
【Human herpesvirus 1 Protein-Protein interactions 】Just some datasets (*)(*)(*)
[Introduction]
Protein-Protein Interactions Table for Human herpesvirus 1
[Link]http://www.stdgen.lanl.gov/cgi-bin/pp.cgi?dbname=hhv1/
-------------------------------------------------------------------------------------------------
【MDSP 】(*)(*)(*)
[Introduction]
Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry
[Link]http://www.mdsp.com/yeast/
-------------------------------------------------------------------------------------------------
【COMBASE 】(*)(*)(*)
[Introduction]
This database is under Construction.In the moment, only the tables and figures are available.
[Link]http://salilab.org/sub-pages/combase.html
-----------------------------------------------------------------------------------------------
【Interact】(*)(*)(*)(*)(*)
[Introduction]
Protein-protein interactions are intrinsic to every cellular process. They form the basis of phenomena such as DNA replication and transcription, metabolism, signal transduction, and cell cycle control. Understanding the role of a protein within a cell relies on discovering the biological context in which it performs its tasks1, therefore knowing the interactions it makes is vital.
Information relating to protein-protein interactions has been spread through many disparate databases. Even sequence databases such as SwissProt2 have interaction information hidden in the free text annotation associated with function. Other databases have taken a more structured approach to storing the interaction data such as DIP 3 and The Yeast Protein Database4.The MIPS5 protein database links to a table of the binary protein interactions of yeast, and a list of the 230 multi-protein complexes.
Object oriented database technology provides a means to fully accommodate and query the data associated with protein interactions. The Object oriented database management system (OODBMS) combines the object oriented methodology with database theory, an alliance which integrates the programming language with the database. The problem of the impedance mismatch of relational database systems, whereby the programming language and the database are incompatible is thus resolved. OODBMS have the ability to express complex and hierarchical relationships, via collections and inheritance and provide flexible data types in the form of objects. This provides an ideal model for the abstraction of real life things such as proteins, experiments and references.
[Link]http://www.bioinf.man.ac.uk/resources/interactpr.shtml
-------------------------------------------------------------------------------------------------
【ProChart Protein-Protein Interaction Database】(*)(*)(*)
[Introduction]
Researchers can do it all with AxCell Bioscience抯 ProChart protein-protein interaction database, coupled with the GenoMax Protein-Protein Interaction Analysis module.
[Link]http://www.informaxinc.com/solutions/genomax/prochart.html
-------------------------------------------------------------------------------------------------
【BRITE】(*)(*)(*)
[Introduction]
Biomolecular Relations in Information Transmission and Expression
BRITE is a database of binary relations for computation and comparison of graphs involving genes and proteins. It contains diverse sets of binary relations, including the generalized protein interactions that underlie the KEGG pathway diagrams, systematic experimental data on protein-protein interactions by yeast two-hybrid systems, sequence similarity relations by SSEARCH, expression similarity relations by microarray gene expression profiles, and the cross-reference links between database entries. This is a preliminary version of BRITE for simple retrieval of partners.
[Link]http://www.genome.ad.jp/brite/brite.html
-------------------------------------------------------------------------------------------------
【Allfuse Database】(*)(*)(*)
[Introduction]
Functional Associations of Proteins in Complete Genomes
References:
Enright A.J., Ouzounis C.A.; Genome Biology 2001 2(9):341-347
'Functional Associations of proteins in entire genomes via exhaustive detection of gene fusion'
Enright A.J.,Iliopoulos I., Kyrpides N., Ouzounis C.A.; Nature 402, 86-90 (1999)
'Protein interaction maps for complete genomes based on gene fusion events'
[Link]http://maine.ebi.ac.uk:8000/services/allfuse/
-------------------------------------------------------------------------------------------------
【PIMdb v0.1】(*)(*)(*)
[Introduction]
As part of our project to construct a two-hybrid-generated protein interaction map for most of the ~13,600 proteins encoded by the Drosophila genome, we are building a protein interactions database. In collaboration with Drs. Farshad Fotouhi and Bill Grosky in the Department of Computer Sciences at Wayne State University, we are developing an Oracle 8i database that will facilitate extraction of functional information from the protein interaction data. A link to this database will appear here as soon as it is available. In the meantime, excerpts of our current interaction database (PIMdb v0.1) can be viewed here in tabular form
[Link]http://cmmg.biosci.wayne.edu/finlab/PIMdbv01.htm
-----------------------------------------------------------------------------------------------
【PREDICTOME】(*)(*)(*)
[Introduction]
... is a tool for visualizing the predicted functional associations among genes and proteins in many different organisms. Associations, or gene links, are created using a variety of techniques, both experimental (yeast two-hybrid, immuno-coprecipitation, correlated expression) and computational (gene fusion, chromosomal proximity, gene co-evolution).
... is based on the premise that genes, or their protein products, can be linked using both experimental and computational techniques. Functional information about individual proteins is then assessed in a network context, where characteristics about a protein can be inferred using the functional traits of neighbors, the neighbors of neighbors, etc.
... is intended as a central repository of the predicted links between proteins. The interface also includes modules that facilitate browsing and interpreting these links.
[Link]http://predictome.bu.edu/l
-----------------------------------------------------------------------------------------------
【YEAST PROTEIN COMPLEX DATABASE】(*)(*)(*)
[Introduction]
YEAST PROTEIN COMPLEX DATABASE
[Link]http://yeast.cellzome.com/
-----------------------------------------------------------------------------------------------
【Protein Interaction Facility 】(*)(*)(*)
[Introduction]
The Protein Interaction Facility provides expertise in characterizing macromolecular interactions. Analytical ultracentrifugation, titration calorimetry and optical biosensors are used to define the assembly state, thermodynamics and kinetics of a reaction. The facility operates on a fee-for-service basis for University of Utah scientists as well as external academic and industrial collaborators. Send us an email message if you are interested in using the facility.
[Link]http://www.cores.utah.edu/interaction/
-----------------------------------------------------------------------------------------------
【ProMesh 】
[Introduction]
N/A
[Link]http://www.bit.uq.edu.au/ProMesh/
-----------------------------------------------------------------------------------------------
300贴纪念
即将推出几个分类专业数据库的介绍，这些都是今半年中在nature,science等杂志中频频引用的专业数据库，希望大家能根据所需很好的利用！我们还会跟踪，及时update!
[分类专业数据库介绍 ]蛋白质相互作用数据库分类分类
【原创文章||转载请注明来自丁香园©】
暂时为英文版，中文版编译中ing......
【BIND】 - Biomolecular Interaction Network Database (*)(*)(*)(*)(*)
[Introduction]
We have designed and implemented a new database encompassing the growing network of protein and other biomolecular interactions, called BIND (Biomolecular Interaction Network Database).
This database will span the complexity of interaction information gathered through experimental studies of biomolecular interactions. Interaction information will come from the literature, submitters and other databases.
BIND contains interaction, molecular complex and pathway records.
[Link]http://www.bind.ca
--------------------------------------------------------------------------------
【DIP】 - Database of Interacting Proteins (*)(*)(*)(*)(*)
[Introduction]
DIP (Database of Interacting Proteins) is a database of protein pairs that are known to interact with each other. By interact we mean two amino acid chains that bind to each other for a function. The idea is to provide well defined links between proteins that interact. The database is publicly available on the web and is intended to aid those studying protein-protein interactions, signaling pathways, multiple interactions and complex systems.
[Link]http://dip.doe-mbi.ucla.edu/
--------------------------------------------------------------------------------
【PIM】 - Hybrigenics (*)(*)(*)
[Introduction]
Protein Interaction Maps: PIMs. for whole microbial pathogen genomes or selected cDNA libraries. First PIMs. available:
Helicobacter pylori (example below)
Hepatitis C Virus
Saccharomyces cerevisiae
[Link]http://www.hybrigenics.fr/
--------------------------------------------------------------------------------
【PathCalling Yeast Interaction Database 】(*)(*)(*)
[Introduction]
PathCalling is CuraGen's validated, industrial scale proteomic technology designed to functionally analyze important disease related or drug response proteins. PathCalling is an automated and fully operational technology powered by GeneScape., CuraGen's Internet-based operating portal. PathCalling enables scientists to:
Identify protein-protein interactions on a genome-wide scale - Knowledge of interacting proteins provides insight into the function of important genes, elucidates relevant pathways, and facilitates the identification of potential drug targets for use in developing novel therapeutics
Rapidly interpret protein-protein interactions - Powerful bioinformatics software enables comparative cross-species genomic analysis, accelerating functional assignment and drug target discovery
Traverse up and down pathways - Expanding biological pathways involved in disease and drug response increases knowledge of the system, and enables scientists to identify both genes and proteins not previously associated with disease or drug response
[Link]http://portal.curagen.com/extpc/com.curagen.portal.servlet.Yeast
--------------------------------------------------------------------------------
【MINT】 - a Molecular Interactions Database (*)(*)(*)(*)(*)
[Introduction]
MINT is a database designed to store functional interactions between biological molecules (proteins, RNA, DNA). Beyond cataloguing the formation of binary complexes, MINT was conceived to store other type of functional interactions namely enzymatic modifications of one of the partners. Presently MINT focuses on experimentally verified protein-protein interactions. Both direct and indirect relationships are considered.
MINT consists of entries extracted from the scientific literature by expert curators assisted by 'MINT Assistant' a software that targets abstracts containing interaction information and prsents them to the curator in a user friendly format.
The interaction data can be easily extracted and viewed graphically by 'MINT Viewer'.
[Link]http://cbm.bio.uniroma2.it/mint/
--------------------------------------------------------------------------------
【GRID】 - The General Repository for Interaction Datasets (*)(*)(*)(*)(*)
[Introduction]
The General Repository for Interaction Datasets (GRID) is a database of genetic and physical interactions developed in The Tyers Group at the Samuel Lunenfeld Research Institute at Mount Sinai Hospital. It contains interaction data from many sources, including several genome/proteome-wide studies, the MIPS database, and BIND.
[Link]http://biodata.mshri.on.ca/grid/servlet/Index
--------------------------------------------------------------------------------
【InterPreTS】 - protein interaction prediction through tertiary structure (*)(*)(*)(*)
[Introduction]
InterPreTS (Interaction Prediction through Tertiary Structure) is a web-based tool for predicting protein-protein interactions. Given a pair of query sequences, it first searches for homologues in a database of interacting domains (DBID) of known three-dimensional complex structures. Pairs of sequences homologous to a known interacting pair are scored for how well they preserve the atomic contacts at the interaction interface.
[Link]http://www.russell.embl.de/interprets/
--------------------------------------------------------------------------------
【STRING】 - predicted functional associations among genes/proteins (*)(*)(*)(*)
[Introduction]
STRING is a database of predicted functional associations among genes/proteins.
Genes of similar function tend to be maintained in close neighborhood, tend to be present or absent together, i.e. to have the same phylogenetic occurrence, and can sometimes be found fused into a single gene encoding a combined polypeptide. STRING integrates this information from as many genomes as possible to predict functional links between proteins.
[Link]http://www.bork.embl-heidelberg.de/STRING/
--------------------------------------------------------------------------------
【BID】(*)(*)(*)
[Introduction]
An overflow of information on the characterization of protein-protein interactions at the amino-acid level is continuing to develop with the goal of better understanding protein interfaces. For this reason it is necessary to acquire a protein-protein interaction database in which an enormous number of interactions can be easily accessed.
[Link]http://tsailab.tamu.edu/BID/
--------------------------------------------------------------------------------
【PPID】 (*)(*)(*)
[Introduction]
The Protein-Protein Interaction Database was originally a single-person's attempt to integrate a gamut of biological/bibliographical/molecular data and build a framework which might help understanding how cells orchestrate their protein content in order to become what they are: machines with a purpose. This is based on the simple paradigm that functionality like signal cascades are held together in a close space, thereby allowing specific events to occur without the necessity of passive diffusion and random events. The PPID database arose from the need to interpret Proteomic datasets, which were generated analysing the NMDA-receptor complex (see H. Husi, M. A. Ward, J. S. Choudhary, W. P. Blackstock and S. G. Grant (2000). Proteomic analysis of NMDA receptor-adhesion protein signaling complexes. Nat Neurosci 3, 661-669.). To study these clusters of proteins requires unavoidably the handling of large datasets, which PPID is generally aimed and tailored for. This database is unifying molecular entries across three species, namely human, rat and mouse and is is footed on sequence databases such as SwissProt, EMBL, TrEMBL (translated EMBL sequences) and Unigene and the literature database PubMed. A typical entry in PPID holds up to three general entries for the three species, all protein and gene accession numbers associated with them (assembled from Blast2 searches of the databases) and the OMIM entry as maintained by Johns Hopkins University. Furthermore protein sequence information is also included, together with known and novel splice-variants of each molecule as found by ClustalW sequence alignments. Entry points also include protein-binding information together with the literature reference. The whole database is curated manually to insure accuracy and quality. Querying the database will be possible by online browsing and batch-submission for large datasets holding accession number information, as can be generated using software like Mascot for mass-spectrometry. Cluster-analysis of the submitted datasets in the form of a graphical output will be developed as well as an easy-to-use web-interface.
An interface is currently being built in collaboration with the Department of Informatics (T. Theodosiou and D. Armstrong) and will be deployed soon
[Link]http://www.anc.ed.ac.uk/mscs/PPID/
----------------------------------------------------------------------------------------------
【C. elegans Protein Interactome 】
[Introduction]
This website is now unavailable! --June 13, 2003 Biozy
------------------------------------------------------------------------------------------------
【SPID】Subtilis Protein interaction Database (*)(*)(*)(*)
[Introduction]
To date, the Database Contains 95 Interactions between 68 Proteins.
[Link]http://www-mig.jouy.inra.fr/bdsi/SPiD/
-------------------------------------------------------------------------------------------------
【Mouse Protein-Protein interactions 】Just some datasets (*)(*)(*)
[Introduction]
Just some datasets about mouse protein-protein interaction
http://genome.gsc.riken.go.jp/ppi/
-------------------------------------------------------------------------------------------------
【Human herpesvirus 1 Protein-Protein interactions 】Just some datasets (*)(*)(*)
[Introduction]
Protein-Protein Interactions Table for Human herpesvirus 1
[Link]http://www.stdgen.lanl.gov/cgi-bin/pp.cgi?dbname=hhv1/
-------------------------------------------------------------------------------------------------
【MDSP 】(*)(*)(*)
[Introduction]
Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry
[Link]http://www.mdsp.com/yeast/
-------------------------------------------------------------------------------------------------
【COMBASE 】(*)(*)(*)
[Introduction]
This database is under Construction.In the moment, only the tables and figures are available.
[Link]http://salilab.org/sub-pages/combase.html
-----------------------------------------------------------------------------------------------
【Interact】(*)(*)(*)(*)(*)
[Introduction]
Protein-protein interactions are intrinsic to every cellular process. They form the basis of phenomena such as DNA replication and transcription, metabolism, signal transduction, and cell cycle control. Understanding the role of a protein within a cell relies on discovering the biological context in which it performs its tasks1, therefore knowing the interactions it makes is vital.
Information relating to protein-protein interactions has been spread through many disparate databases. Even sequence databases such as SwissProt2 have interaction information hidden in the free text annotation associated with function. Other databases have taken a more structured approach to storing the interaction data such as DIP 3 and The Yeast Protein Database4.The MIPS5 protein database links to a table of the binary protein interactions of yeast, and a list of the 230 multi-protein complexes.
Object oriented database technology provides a means to fully accommodate and query the data associated with protein interactions. The Object oriented database management system (OODBMS) combines the object oriented methodology with database theory, an alliance which integrates the programming language with the database. The problem of the impedance mismatch of relational database systems, whereby the programming language and the database are incompatible is thus resolved. OODBMS have the ability to express complex and hierarchical relationships, via collections and inheritance and provide flexible data types in the form of objects. This provides an ideal model for the abstraction of real life things such as proteins, experiments and references.
[Link]http://www.bioinf.man.ac.uk/resources/interactpr.shtml
-------------------------------------------------------------------------------------------------
【ProChart Protein-Protein Interaction Database】(*)(*)(*)
[Introduction]
Researchers can do it all with AxCell Bioscience抯 ProChart protein-protein interaction database, coupled with the GenoMax Protein-Protein Interaction Analysis module.
[Link]http://www.informaxinc.com/solutions/genomax/prochart.html
-------------------------------------------------------------------------------------------------
【BRITE】(*)(*)(*)
[Introduction]
Biomolecular Relations in Information Transmission and Expression
BRITE is a database of binary relations for computation and comparison of graphs involving genes and proteins. It contains diverse sets of binary relations, including the generalized protein interactions that underlie the KEGG pathway diagrams, systematic experimental data on protein-protein interactions by yeast two-hybrid systems, sequence similarity relations by SSEARCH, expression similarity relations by microarray gene expression profiles, and the cross-reference links between database entries. This is a preliminary version of BRITE for simple retrieval of partners.
[Link]http://www.genome.ad.jp/brite/brite.html
-------------------------------------------------------------------------------------------------
【Allfuse Database】(*)(*)(*)
[Introduction]
Functional Associations of Proteins in Complete Genomes
References:
Enright A.J., Ouzounis C.A.; Genome Biology 2001 2(9):341-347
'Functional Associations of proteins in entire genomes via exhaustive detection of gene fusion'
Enright A.J.,Iliopoulos I., Kyrpides N., Ouzounis C.A.; Nature 402, 86-90 (1999)
'Protein interaction maps for complete genomes based on gene fusion events'
[Link]http://maine.ebi.ac.uk:8000/services/allfuse/
-------------------------------------------------------------------------------------------------
【PIMdb v0.1】(*)(*)(*)
[Introduction]
As part of our project to construct a two-hybrid-generated protein interaction map for most of the ~13,600 proteins encoded by the Drosophila genome, we are building a protein interactions database. In collaboration with Drs. Farshad Fotouhi and Bill Grosky in the Department of Computer Sciences at Wayne State University, we are developing an Oracle 8i database that will facilitate extraction of functional information from the protein interaction data. A link to this database will appear here as soon as it is available. In the meantime, excerpts of our current interaction database (PIMdb v0.1) can be viewed here in tabular form
[Link]http://cmmg.biosci.wayne.edu/finlab/PIMdbv01.htm
-----------------------------------------------------------------------------------------------
【PREDICTOME】(*)(*)(*)
[Introduction]
... is a tool for visualizing the predicted functional associations among genes and proteins in many different organisms. Associations, or gene links, are created using a variety of techniques, both experimental (yeast two-hybrid, immuno-coprecipitation, correlated expression) and computational (gene fusion, chromosomal proximity, gene co-evolution).
... is based on the premise that genes, or their protein products, can be linked using both experimental and computational techniques. Functional information about individual proteins is then assessed in a network context, where characteristics about a protein can be inferred using the functional traits of neighbors, the neighbors of neighbors, etc.
... is intended as a central repository of the predicted links between proteins. The interface also includes modules that facilitate browsing and interpreting these links.
[Link]http://predictome.bu.edu/l
-----------------------------------------------------------------------------------------------
【YEAST PROTEIN COMPLEX DATABASE】(*)(*)(*)
[Introduction]
YEAST PROTEIN COMPLEX DATABASE
[Link]http://yeast.cellzome.com/
-----------------------------------------------------------------------------------------------
【Protein Interaction Facility 】(*)(*)(*)
[Introduction]
The Protein Interaction Facility provides expertise in characterizing macromolecular interactions. Analytical ultracentrifugation, titration calorimetry and optical biosensors are used to define the assembly state, thermodynamics and kinetics of a reaction. The facility operates on a fee-for-service basis for University of Utah scientists as well as external academic and industrial collaborators. Send us an email message if you are interested in using the facility.
[Link]http://www.cores.utah.edu/interaction/
-----------------------------------------------------------------------------------------------
【ProMesh 】
[Introduction]
N/A
[Link]http://www.bit.uq.edu.au/ProMesh/
-----------------------------------------------------------------------------------------------
300贴纪念
10 47 1
