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OKCAM

http://okcam.cbi.pku.edu.cn/

Description :
Ontology-based Knowledgebase for Cell Adhesion Molecules

FunSimMat

http://funsimmat.bioinf.mpi-inf.mpg.de/

Description :
Gene Ontology-based functional similarity values for proteins and protein families

GOPaD

http://bcl.med.harvard.edu/proj/gopart

Description :
The Gene Ontology Partition Database (GO PaD) contains data from an information theoretic analysis of the Gene Ontology (GO) that maximizes information content for gene enrichment and functional analysis. The GO Partition Database was designed to feature ontology partitions with GO terms of similar specificity. The GO partitions comprise varying numbers of GO nodes and present relevant information theoretic statistics, so researchers can choose to analyze gene datasets at arbitrary desired levels of specificity. The GO Partition Database features GO partitions for functional analysis of genes from human and ten other commonly-studied organisms, based on surveying nearly 132,000 genes. The database site (http://bcl.emed.harvard.edu/proj/gopart) also includes an online tutorial.

Aknowledgement :
This work was supported in part by a fellowship from the Whitaker Foundation, the MIT Undergraduate Research Opportunity Program, the National Library of Medicine (NLM/NIH) under grant 5T15LM007092, and the National Human Genome Research Institute (NHGRI/NIH) under grant 1R01HG003354.

References :
1. G. Alterovitz, M. Xiang, M. Mohan, and M. F. Ramoni (2007). GO PaD: The Gene Ontology Partition Database, Nucleic Acids Res. 35: in press

Onto-CC

http://gps-tools2.wustl.edu/onto-cc/index.html

Description :
Gene Ontology Conceptual Clustering (Onto-CC) is a tool for independent validation of gene co-expression based on GO clusters.

GOEAST

http://omicslab.genetics.ac.cn/GOEAST/

Description :
Gene Ontology Enrichment Analysis (GOEAST) is a toolkit for the identification of over-represented GO terms in a given gene set. Distinguishing features include: capacity to analyze data from various sources and from multiple species, and the capacity to cross compare GO enriched terms across experiments to identify correlations.

SerbGO

http://estbioinfo.stat.ub.es/apli/serbgo

Description :
Searching for the best GO tool (SerbGO) helps users select the GO annotation or list analysis tools which best suit their needs. SerbGO may also be used to compare the capabilities of the various GO tools in the context of the users' experiment.

MassNet

http://massnet.kr/

Description :
MassNet web server provides comprehensive functional annotation of mass spectrometry data. Annotation includes physico-chemical analysis, KEGG pathway assignment, GO mapping, and protein-protein interaction prediction.

FFPred

http://bioinf.cs.ucl.ac.uk/ffpred/

Description :
Using a machine learning approach, FFPred server predicts protein function using protein features scanned against a library of over 300 Gene Ontology annotation terms. FFPred has the capacity to annotate distant homologues and orphan protein sequences.

YOGY

http://www.sanger.ac.uk/PostGenomics/S_pombe/YOGY/

Description :
Eukaryotic Orthology (YOGY) is a resource for retrieving orthologous proteins from nine eukaryotic organisms. Using a gene or protein identifier as a query, this database provides comprehensive, combined information on orthologs in other species using data from five independent resources: KOGs, Inparanoid, Homologene, OrthoMCL, and a table of curated orthologs between budding yeast and fission yeast. Associated Gene Ontology (GO) terms of orthologs can also beretrieved.

Proteome Analyst

http://www.cs.ualberta.ca/~bioinfo/PA/

Description :
Proteome Analyst is a high-throughput tool for predicting properties for each protein in a proteome. The user provides a proteome in fasta format, and the system employs Psi-blast, Psipred and Modeller to predict protein function and subcellular localization. Proteome Analyst uses machine-learned classifiers to predict things such as GO molecular function. User-supplied training data can also be used to create custom classifiers.

TIGRFAMs

http://www.tigr.org/TIGRFAMs

Description :
TIGRFAMs is a collection of manually curated protein families consisting of hidden Markov models (HMMs), multiple sequence alignments, Gene Ontology (GO) assignments, commentary, literature references and pointers to related TIGRFAMs, Pfam and InterPro models. These models are designed to support both automated and manually curated annotation of genomes. TIGRFAMs contains models of full-length proteins as well as domains at the levels of superfamilies, subfamilies and equivalogs (which are sets of homologous proteins that are conserved with respect to function since their last common ancestor). TIGRFAMs models are allowed to be heirarchically nested to yield the maximum amount of information for the annotation process. TIGRFAMs are thus complementary to Pfam models which are designed to represent non-overlapping structural domains. The TIGRFAMs database is integrated with the prokaryotic genome annotation pipeline at TIGR and thus is being constantly updated with respect to new information on protein function, model scope and performance. TIGRFAMs currently contains over 1600 protein families, having doubled in size in two years. TIGRFAMs is available for searching or downloading at www.tigr.org/TIGRFAMs.

Recent develoments :
Since the TIGRFAMs database was first described in the January 2001 database issue of Nucleic Acids Research, the number of models in TIGRFAMs has doubled to over 1600. A large number of entries have been assigned specific Gene Ontology (GO) terms. TIGRFAMs links are now reported in the SwissProt database. TIGRFAMs has been incorporated into InterPro; InterPro entries based on or including TIGRFAMs entries show parent/child and contains/found in relationships with entries from Pfam, SMART, and other protein classification databases. Continued use of TIGRFAMs in microbial annotation at TIGR has provided steady feedback for improving the accuracy of existing models while new genomes and new functional characterizationns became available. TIGRFAMs models now hit nearly twenty per cent of the proteins of typical newly sequenced bacterial genomes. The equivalog subset can be expected to make about 400 high-confidence specific functional assignments for a typical new 4-megabase bacterial genome.

AgBase

http://www.agbase.msstate.edu/

Description :
AgBase is a curated, open-source, Web-accessible resource for functional analysis of agricultural plant and animal gene products. Our long-term goal is to serve the needs of the agricultural research communities by facilitating post-genome biology for agriculture researchers and for those researchers primarily using agricultural species as biomedical models. We have developed a novel method for facilitating structural annotation of genomes, "expressed protein sequence tags" (ePSTs) and these ePSTs are provided through AgBase. We use controlled vocabularies developed by the Gene Ontology (GO) Consortium to describe molecular function, biological process, and cellular component for genes and gene products in agricultural species. We provide tools designed to assist with the analysis of proteomics data and tools to evaluate experimental datasets using the GO.

Recent develoments :
AgBase has recently provided a mechanism for researchers to add or request GO annotations for agriculturally important species.
Statistics for the GO annotations provided by AgBase and the AgBase Journal Database (JDB) used by AgBase biocurators for GO annotations are now available. The "expressed protein sequence tags" (ePSTs) database can now be searched using Blast queries.

Aknowledgement :
We acknowledge the following groups for their help and support: The GO Consortium, especially DictyBase for providing the database schema and for technical assistance with implementation, MGI for providing training and continued support with manual curation issues and GOA for allowing us access to their tools and for their continued help, support and patience. AgBase has received financial support from the Mississippi State University Office of Research, Division of Agriculture and Forestry, College of Veterinary Medicine, Bagley College of Engineering and Life Sciences and Biotechnology Institute. AgBase is also supported by grants from the United States Department of Agriculture and the National Science Foundation.

References :
1. McCarthy, F. M., N. Wang, G. B. Magee, B. Nanduri, M. L. Lawrence, E. B. Camon, D. G. Barrell, D. P. Hill, M. E. Dolan, W. P. Williams, D. S. Luthe, S. M. Bridges, and S. C. Burgess (2006). AgBase: a functional genomics resource for agriculture." BMC Genomics 7:229.

Patome

http://www.patome.org/

Description :
Patome contains biological sequence data disclosed in patents and published applications, as well as their analysis information. The analysis is divided into two steps. The first is an annotation step in which the disclosed sequences were annotated with RefSeq database. The second is an association step where the sequences were linked to Entrez Gene, OMIM, and GO databases, and their results were saved as a gene-patent table. Patome is available at http://www.patome.org/; the information is updated bimonthly.

Aknowledgement :
B. Lee thanks Dr. YoungGyun Cho at the Korean Intellectual Property Office (KIPO) for helpful discussion. We especially thank Maryana Bhak for editing this manuscript. This work was supported by the Korean Ministry of Science and Technology (MOST) under grant number M10407010001-04N0701-00110.

PA-GOSUB

http://www.cs.ualberta.ca/~bioinfo/PA/

Description :
Protein sequences from model organisms, GO assignment and subcellular localization

Plant Ontology database

http://www.plantontology.org/

Description :
The Plant Ontology (PO, http://www.plantontology.org) is a collaborative effort among several plant databases and experts in plant systematics, botany and genomics. The goal of the PO is to develop simple yet robust and extensible controlled vocabularies that accurately reflect the biology of plant structures (morphology and anatomy) and developmental stages. Once implemented, these provide a network of vocabularies linked by relationships (ontology) to facilitate queries that cut across data sets within a database or between multiple databases. Using the ontology browser (http://www.plantontology.org/amigo/go.cgi), over 5000 gene annotations from Arabidopsis, maize and rice can be searched. Using the same browser a user can also search the plant structure (e.g. root hair) and growth stage (e.g. reproductive stage) terms. Learn how to browse and use the ontologies by visiting http://www.plantontology.org/docs/otherdocs/tutorials.html. The vocabularies, annotations, mappings and the database can be downloaded by following the instructions provided at http://www.plantontology.org/download/download.html. Learn more about the ontologies, design and development aspects by visiting http://www.plantontology.org/docs/docs.html

Recent develoments :
The current version of the ontology integrates diverse vocabularies used to describe Arabidopsis, maize, rice, Triticeae, legumes and tomato plant anatomy, morphology, growth and developmental stages. Using the ontology browser (http://www.plantontology.org/amigo/go.cgi), over 5000 gene annotations from three species specific databases, The Arabidopsis Information Resource (TAIR, http://www.arabiidopsis.org) for Arabidopsis, Gramene (http://www.gramene.org) for rice and MaizeGDB (http://www.maizegdb.org) for maize, can now be queried and retrieved.

Aknowledgement :
We gratefully acknowledge the Gene Ontology Consortium for making the ontology browser (AmiGO), editor (DAG-Edit), Obol tool and database software available and for help with modifications and implementation. We are grateful to many researchers, reviewers, database groups and curators for help in reviewing, adding new terms to the ontology and using them in their annotation work. This work is supported by the National Science Foundation award (Grant No. 0321666) to the Plant Ontology Consortium and USDA-ARS, USA.

References :
1. The Plant Ontology Consortium. (2002) The Plant Ontology Consortium and Plant Ontologies. Comparative and Functional Genomics, 3: 137-142.
2. P. Jaiswal, S. Avraham, K. Ilic, E.A. Kellogg, A. Pujar, L. Reiser, R.Y. Seung, M.M. Sachs, M. Schaeffer, L. Stein et al. (2005) Plant Ontology (PO): a controlled vocabulary of plant structures and growth stages. Comparative and Functional Genomics, 6: 388-397.

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