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404
STRING v9.1: protein-protein interaction networks, with increased coverage and integration
- Nucleic Acids Res
, 2013
"... Complete knowledge of all direct and indirect inter-actions between proteins in a given cell would represent an important milestone towards a com-prehensive description of cellular mechanisms and functions. Although this goal is still elusive, consid-erable progress has been made—particularly for ce ..."
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Cited by 183 (9 self)
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Complete knowledge of all direct and indirect inter-actions between proteins in a given cell would represent an important milestone towards a com-prehensive description of cellular mechanisms and functions. Although this goal is still elusive, consid-erable progress has been made—particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available inter-action data is desirable, including lower-quality data and/or computational predictions. The STRING database
Reactome: a database of reactions, pathways and biological processes.Nucl Acids Res 39: D691–7
, 2011
"... Reactome ..."
C: The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013. Nucleic Acids Res 2013, 41(Database issue):456–463
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EcoCyc: a comprehensive view of Escherichia coli biology. Nucleic Acids Res
, 2009
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WormBase: a comprehensive resource for nematode research
- Nucleic Acids Res
, 2010
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The National Center for Biotechnology Information’s Protein Clusters Database
- Nucleic Acids Res
, 2009
"... Rapid increases in DNA sequencing capabilities have led to a vast increase in the data generated from prokaryotic genomic studies, which has been a boon to scientists studying micro-organism evolution and to those who wish to understand the biological underpinnings of microbial systems. The NCBI Pro ..."
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Cited by 51 (3 self)
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Rapid increases in DNA sequencing capabilities have led to a vast increase in the data generated from prokaryotic genomic studies, which has been a boon to scientists studying micro-organism evolution and to those who wish to understand the biological underpinnings of microbial systems. The NCBI Protein Clusters Database (ProtClustDB) has been created to efficiently maintain and keep the deluge of data up to date. ProtClustDB contains both curated and uncurated clusters of proteins grouped by sequence similarity. The May 2008 release contains a total of 285 386 clusters derived from over 1.7 million proteins encoded by 3806 nt sequences from the RefSeq collection of complete chromosomes and plasmids from four major groups: prokaryotes, bacteriophages and the mitochondrial and chloroplast organelles. There are 7180 clusters containing 376 513 proteins with curated gene and protein functional annotation. PubMed identifiers and external cross references are collected for all clusters and provide additional information resources. A suite of web tools is available to explore more detailed information, such as multiple alignments, phylogenetic trees and genomic neighborhoods. ProtClustDB provides an efficient method to aggregate gene and protein annotation for researchers and is available at
EcoCyc: a comprehensive database of Escherichia coli biology
- Nucleic Acids Res
, 2011
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C: Scalable metabolic reconstruction for metagenomic data and the human microbiome
- 19th Annual International Conference on Intelligent Systems for Molecular Biology; 17-19 July 2011: Vienna International Society for Computational Biology
"... Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities ’ metagenomes provides information complementary to organismal ..."
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Cited by 38 (2 self)
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Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities ’ metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large
TSGene: a web resource for tumor suppressor genes
- Nucleic Acids Res
, 2005
"... Tumor suppressor genes (TSGs) are guardian genes that play important roles in controlling cell prolifer-ation processes such as cell-cycle checkpoints and inducing apoptosis. Identification of these genes and understanding their functions are critical for further investigation of tumorigenesis. So f ..."
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Cited by 34 (2 self)
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Tumor suppressor genes (TSGs) are guardian genes that play important roles in controlling cell prolifer-ation processes such as cell-cycle checkpoints and inducing apoptosis. Identification of these genes and understanding their functions are critical for further investigation of tumorigenesis. So far, many studies have identified numerous TSGs and illustrated their functions in various types of tumors or normal samples. Furthermore, accumu-lating evidence has shown that non-coding RNAs can act as TSGs to prevent the tumorigenesis processes. Therefore, there is a growing demand to integrate TSGs with large-scale experimental evidence (e.g. gene expression and epigenetic sig-natures) to provide a comprehensive resource for further investigation of TSGs and their molecular mechanisms in cancer. To achieve this goal, we first developed a comprehensive literature-based database called TSGene (tumor suppressor gene database), freely available at
