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Open AccessJournal ArticleDOI

Phytozome: a comparative platform for green plant genomics

TLDR
Phytozome provides a view of the evolutionary history of every plant gene at the level of sequence, gene structure, gene family and genome organization, while at the same time providing access to the sequences and functional annotations of a growing number of complete plant genomes.
Abstract
The number of sequenced plant genomes and associated genomic resources is growing rapidly with the advent of both an increased focus on plant genomics from funding agencies, and the application of inexpensive next generation sequencing. To interact with this increasing body of data, we have developed Phytozome (http://www.phytozome.net), a comparative hub for plant genome and gene family data and analysis. Phytozome provides a view of the evolutionary history of every plant gene at the level of sequence, gene structure, gene family and genome organization, while at the same time providing access to the sequences and functional annotations of a growing number (currently 25) of complete plant genomes, including all the land plants and selected algae sequenced at the Joint Genome Institute, as well as selected species sequenced elsewhere. Through a comprehensive plant genome database and web portal, these data and analyses are available to the broader plant science research community, providing powerful comparative genomics tools that help to link model systems with other plants of economic and ecological importance.

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Journal ArticleDOI

OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy

TL;DR: A novel orthogroups inference algorithm called OrthoFinder is provided that solves a previously undetected gene length bias in orthogroup inference, resulting in significant improvements in accuracy and utility.
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psRNATarget: a plant small RNA target analysis server

TL;DR: The psRNATarget as mentioned in this paper target analysis server is designed for high-throughput analysis of next-generation data with an efficient distributed computing back-end pipeline that runs on a Linux cluster.
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agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update.

TL;DR: The updated agriGO that has a largely expanded number of supporting species and datatypes and more visualization features were added to the platform, including SEACOMPARE, direct acyclic graph (DAG) and Scatter Plots, which can be merged by choosing any significant GO term.
Journal ArticleDOI

SIFT missense predictions for genomes

TL;DR: The scope of genomic predictions is expanded, with predictions available for more than 200 organisms, and the SIFT 4G algorithm, which is a faster version of SIFT that enables practical computations on reference genomes, is described.
References
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Journal ArticleDOI

MUSCLE: multiple sequence alignment with high accuracy and high throughput

TL;DR: MUSCLE is a new computer program for creating multiple alignments of protein sequences that includes fast distance estimation using kmer counting, progressive alignment using a new profile function the authors call the log-expectation score, and refinement using tree-dependent restricted partitioning.
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Gene Ontology: tool for the unification of biology

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.
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KEGG: Kyoto Encyclopedia of Genes and Genomes

TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
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The Pfam protein families database

TL;DR: The definition and use of family-specific, manually curated gathering thresholds are explained and some of the features of domains of unknown function (also known as DUFs) are discussed, which constitute a rapidly growing class of families within Pfam.
Journal ArticleDOI

Identification of common molecular subsequences.

TL;DR: This letter extends the heuristic homology algorithm of Needleman & Wunsch (1970) to find a pair of segments, one from each of two long sequences, such that there is no other Pair of segments with greater similarity (homology).
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