The PhyloFacts FAT-CAT web server: ortholog identification and function prediction using fast approximate tree classification
نویسندگان
چکیده
The PhyloFacts 'Fast Approximate Tree Classification' (FAT-CAT) web server provides a novel approach to ortholog identification using subtree hidden Markov model-based placement of protein sequences to phylogenomic orthology groups in the PhyloFacts database. Results on a data set of microbial, plant and animal proteins demonstrate FAT-CAT's high precision at separating orthologs and paralogs and robustness to promiscuous domains. We also present results documenting the precision of ortholog identification based on subtree hidden Markov model scoring. The FAT-CAT phylogenetic placement is used to derive a functional annotation for the query, including confidence scores and drill-down capabilities. PhyloFacts' broad taxonomic and functional coverage, with >7.3 M proteins from across the Tree of Life, enables FAT-CAT to predict orthologs and assign function for most sequence inputs. Four pipeline parameter presets are provided to handle different sequence types, including partial sequences and proteins containing promiscuous domains; users can also modify individual parameters. PhyloFacts trees matching the query can be viewed interactively online using the PhyloScope Javascript tree viewer and are hyperlinked to various external databases. The FAT-CAT web server is available at http://phylogenomics.berkeley.edu/phylofacts/fatcat/.
منابع مشابه
Berkeley Phylogenomics Group web servers: resources for structural phylogenomic analysis
Phylogenomic analysis addresses the limitations of function prediction based on annotation transfer, and has been shown to enable the highest accuracy in prediction of protein molecular function. The Berkeley Phylogenomics Group provides a series of web servers for phylogenomic analysis: classification of sequences to pre-computed families and subfamilies using the PhyloFacts Phylogenomic Encyc...
متن کاملBerkeley PHOG: PhyloFacts orthology group prediction web server
Ortholog detection is essential in functional annotation of genomes, with applications to phylogenetic tree construction, prediction of protein-protein interaction and other bioinformatics tasks. We present here the PHOG web server employing a novel algorithm to identify orthologs based on phylogenetic analysis. Results on a benchmark dataset from the TreeFam-A manually curated orthology databa...
متن کاملAutomated Protein Subfamily Identification and Classification
Function prediction by homology is widely used to provide preliminary functional annotations for genes for which experimental evidence of function is unavailable or limited. This approach has been shown to be prone to systematic error, including percolation of annotation errors through sequence databases. Phylogenomic analysis avoids these errors in function prediction but has been difficult to...
متن کاملApplication of soil properties, auxiliary parameters, and their combination for prediction of soil classes using decision tree model
Soil classification systems are very useful for a simple and fast summarization of soil properties. These systems indicate the method for data summarization and facilitate connections among researchers, engineers, and other users. One of the practical systems for soil classification is Soil Taxonomy (ST). As determining soil classes for an entire area is expensive, time-consuming, and almost ...
متن کاملINTREPID—INformation-theoretic TREe traversal for Protein functional site IDentification
MOTIVATION Identification of functionally important residues in proteins plays a significant role in biological discovery. Here, we present INTREPID--an information-theoretic approach for functional site identification that exploits the information in large diverse multiple sequence alignments (MSAs). INTREPID uses a traversal of the phylogeny in combination with a positional conservation score...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 41 شماره
صفحات -
تاریخ انتشار 2013