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While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Description<\/jats:title>\n            <jats:p>The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga <jats:italic>Chlamydomonas reinhardtii<\/jats:italic>, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps and batch gene identifier conversion.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>The Algal Functional Annotation Tool aims to provide an integrated data-mining environment for algal genomics by combining data from multiple annotation databases into a centralized tool. This site is designed to expedite the process of functional annotation and the interpretation of gene lists, such as those derived from high-throughput RNA-seq experiments. The tool is publicly available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/pathways.mcdb.ucla.edu\" ext-link-type=\"uri\">http:\/\/pathways.mcdb.ucla.edu<\/jats:ext-link>.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-12-282","type":"journal-article","created":{"date-parts":[[2011,7,13]],"date-time":"2011-07-13T06:21:26Z","timestamp":1310538086000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":76,"title":["Algal Functional Annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data"],"prefix":"10.1186","volume":"12","author":[{"given":"David","family":"Lopez","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Casero","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shawn J","family":"Cokus","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabeeha S","family":"Merchant","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matteo","family":"Pellegrini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2011,7,12]]},"reference":[{"key":"4657_CR1","series-title":"Nucleic Acids Res","volume-title":"KEGG for representation and analysis of molecular networks involving diseases and drugs","author":"M Kanehisa","year":"2010","unstructured":"Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M: KEGG for representation and analysis of molecular networks involving diseases and drugs. 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