MIPS: analysis and annotation of proteins from whole genomes
TL;DR: The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information and develops databases covering computable information such as the basic evolutionary relations among all genes.
Abstract: The Munich Information Center for Protein Sequences (MIPS-GSF), Neuherberg, Germany, provides protein sequence-related information based on whole-genome analysis. The main focus of the work is directed toward the systematic organization of sequence-related attributes as gathered by a variety of algorithms, primary information from experimental data together with information compiled from the scientific literature. MIPS maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the database of complete cDNAs (German Human Genome Project, NGFN), the database of mammalian protein-protein interactions (MPPI), the database of FASTA homologies (SIMAP), and the interface for the fast retrieval of protein-associated information (QUIPOS). The Arabidopsis thaliana database, the rice database, the plant EST databases (MATDB, MOsDB, SPUTNIK), as well as the databases for the comprehensive set of genomes (PEDANT genomes) are described elsewhere in the 2003 and 2004 NAR database issues, respectively. All databases described, and the detailed descriptions of our projects can be accessed through the MIPS web server (http://mips.gsf.de).
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TL;DR: BioGRID is a freely accessible database of physical and genetic interactions that includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens.
Abstract: Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at http://www.thebiogrid.org. BioGRID release version 2.0 includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. Over 30 000 interactions have recently been added from 5778 sources through exhaustive curation of the Saccharomyces cerevisiae primary literature. An internally hyper-linked web interface allows for rapid search and retrieval of interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files and PSI-MI XML. Pre-computed graphical layouts of interactions are available in a variety of file formats. User-customized graphs with embedded protein, gene and interaction attributes can be constructed with a visualization system called Osprey that is dynamically linked to the BioGRID.
3,794 citations
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...A number of interaction databases, including BIND (6), DIP (7), HPRD (8), IntAct (9), MINT (10), and MIPS (11), provide a variety of datasets and analysis tools....
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TL;DR: T tandem affinity purification was used to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae to identify protein–protein interactions, which will help future studies on individual proteins as well as functional genomics and systems biology.
Abstract: Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.
2,975 citations
TL;DR: This study reports the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry and provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.
Abstract: Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.
2,640 citations
TL;DR: A large, highly connected network of interacting pairs of human proteins was identified, characterizing ANP32A and CRMP1 as modulators of Wnt signaling and two novel Axin-1 interactions were validated experimentally.
2,382 citations
Cites background or methods from "MIPS: analysis and annotation of pr..."
..., 2004), and Sc (Mewes et al., 2004) and determined the appearance of orthologous Y2H interactions in interaction loop motifs....
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...Next, we merged these data sets with published model organism PPI data from Dm (Giot et al., 2003), Ce (Li et al., 2004), and Sc (Mewes et al., 2004) and determined the appearance of orthologous Y2H interactions in interaction loop motifs....
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TL;DR: In this article, the authors introduce a class of variance allocation models for pairwise measurements, called mixed membership stochastic blockmodels, which combine global parameters that instantiate dense patches of connectivity (blockmodel) with local parameters (mixed membership), and develop a general variational inference algorithm for fast approximate posterior inference.
Abstract: Consider data consisting of pairwise measurements, such as presence or absence of links between pairs of objects. These data arise, for instance, in the analysis of protein interactions and gene regulatory networks, collections of author-recipient email, and social networks. Analyzing pairwise measurements with probabilistic models requires special assumptions, since the usual independence or exchangeability assumptions no longer hold. Here we introduce a class of variance allocation models for pairwise measurements: mixed membership stochastic blockmodels. These models combine global parameters that instantiate dense patches of connectivity (blockmodel) with local parameters that instantiate node-specific variability in the connections (mixed membership). We develop a general variational inference algorithm for fast approximate posterior inference. We demonstrate the advantages of mixed membership stochastic blockmodels with applications to social networks and protein interaction networks.
1,803 citations
References
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TL;DR: The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.
Abstract: Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
35,225 citations
TL;DR: This work presents a novel approach called TRIBE-MCL for rapid and accurate clustering of protein sequences into families based on precomputed sequence similarity information that has been rigorously tested and validated on a number of very large databases.
Abstract: Detection of protein families in large databases is one of the principal research objectives in structural and functional genomics. Protein family classification can significantly contribute to the delineation of functional diversity of homologous proteins, the prediction of function based on domain architecture or the presence of sequence motifs as well as comparative genomics, providing valuable evolutionary insights. We present a novel approach called TRIBE-MCL for rapid and accurate clustering of protein sequences into families. The method relies on the Markov cluster (MCL) algorithm for the assignment of proteins into families based on precomputed sequence similarity information. This novel approach does not suffer from the problems that normally hinder other protein sequence clustering algorithms, such as the presence of multi-domain proteins, promiscuous domains and fragmented proteins. The method has been rigorously tested and validated on a number of very large databases, including SwissProt, InterPro, SCOP and the draft human genome. Our results indicate that the method is ideally suited to the rapid and accurate detection of protein families on a large scale. The method has been used to detect and categorise protein families within the draft human genome and the resulting families have been used to annotate a large proportion of human proteins.
3,468 citations
"MIPS: analysis and annotation of pr..." refers methods in this paper
...For instance, Markov-Random-Field clustering methods such as MCL (14) can be applied to detect protein families....
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TL;DR: The TRANSFAC database on eukaryotic transcriptional regulation, comprising data on transcription factors, their target genes and regulatory binding sites, has been extended and further developed, both in number of entries and in the scope and structure of the collected data.
Abstract: The TRANSFAC database on eukaryotic transcriptional regulation, comprising data on transcription factors, their target genes and regulatory binding sites, has been extended and further developed, both in number of entries and in the scope and structure of the collected data. Structured fields for expression patterns have been introduced for transcription factors from human and mouse, using the CYTOMER database on anatomical structures and developmental stages. The functionality of Match, a tool for matrix-based search of transcription factor binding sites, has been enhanced. For instance, the program now comes along with a number of tissue-(or state-)specific profiles and new profiles can be created and modified with Match Profiler. The GENE table was extended and gained in importance, containing amongst others links to LocusLink, RefSeq and OMIM now. Further, (direct) links between factor and target gene on one hand and between gene and encoded factor on the other hand were introduced. The TRANSFAC public release is available at http://www.gene-regulation.com. For yeast an additional release including the latest data was made available separately as TRANSFAC Saccharomyces Module (TSM) at http://transfac.gbf.de. For CYTOMER free download versions are available at http://www.biobase.de:8080/index.html.
2,143 citations
"MIPS: analysis and annotation of pr..." refers background in this paper
...[TRANSFAC (3)] and metabolic pathways are either part of the core yeast database or can be retrieved using the BioRS data integration system....
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TL;DR: STRING contains a unique scoring-framework based on benchmarks of the different types of associations against a common reference set, integrated in a single confidence score per prediction, facilitating the analysis of modularity in biological processes.
Abstract: Functional links between proteins can often be inferred from genomic associations between the genes that encode them: groups of genes that are required for the same function tend to show similar species coverage, are often located in close proximity on the genome (in prokaryotes), and tend to be involved in gene-fusion events. The database STRING is a precomputed global resource for the exploration and analysis of these associations. Since the three types of evidence differ conceptually, and the number of predicted interactions is very large, it is essential to be able to assess and compare the significance of individual predictions. Thus, STRING contains a unique scoring-framework based on benchmarks of the different types of associations against a common reference set, integrated in a single confidence score per prediction. The graphical representation of the network of inferred, weighted protein interactions provides a high-level view of functional linkage, facilitating the analysis of modularity in biological processes. STRING is updated continuously, and currently contains 261 033 orthologs in 89 fully sequenced genomes. The database predicts functional interactions at an expected level of accuracy of at least 80% for more than half of the genes; it is online at http://www.bork.embl-heidelberg.de/STRING/.
1,802 citations
"MIPS: analysis and annotation of pr..." refers methods in this paper
...An important contribution of novel experimental techniques during the last few years has been the computational analysis of modules and networks based on the combination of independent types of information (4,5)....
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Massachusetts Institute of Technology1, University of California, Riverside2, University of Oregon3, University of Edinburgh4, Celera Corporation5, Texas A&M University6, University of New Mexico7, University of Colorado Denver8, University of Kansas9, University of Florida10, Hebrew University of Jerusalem11, University of Düsseldorf12, Rockefeller University13, Technische Universität München14, University of Kentucky15, University of Texas at Austin16, J. Craig Venter Institute17, University of California, Berkeley18, University of California, Los Angeles19, Sapienza University of Rome20, Flinders University21, Ohio State University22, University of Arizona23, University of Missouri–Kansas City24, Dartmouth College25, University of Leeds26, California State Polytechnic University, Pomona27, Oregon Health & Science University28
TL;DR: A high-quality draft sequence of the N. crassa genome is reported, suggesting that RIP has had a profound impact on genome evolution, greatly slowing the creation of new genes through genomic duplication and resulting in a genome with an unusually low proportion of closely related genes.
Abstract: Neurospora crassa is a central organism in the history of twentieth-century genetics, biochemistry and molecular biology. Here, we
report a high-quality draft sequence of the N. crassa genome. The approximately 40-megabase genome encodes about 10,000
protein-coding genes—more than twice as many as in the fission yeast Schizosaccharomyces pombe and only about 25% fewer
than in the fruitfly Drosophila melanogaster. Analysis of the gene set yields insights into unexpected aspects of Neurospora biology
including the identification of genes potentially associated with red light photobiology, genes implicated in secondary metabolism,
and important differences in Ca21 signalling as compared with plants and animals. Neurospora possesses the widest array of
genome defence mechanisms known for any eukaryotic organism, including a process unique to fungi called repeat-induced
point mutation (RIP). Genome analysis suggests that RIP has had a profound impact on genome evolution, greatly slowing the
creation of new genes through genomic duplication and resulting in a genome with an unusually low proportion of closely related
genes.
1,659 citations