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• W2792091229 abstract "Recent times have seen an enormous growth of omics data, of which high-throughput gene expression data are arguably the most important from a functional perspective. Despite huge improvements in computational techniques for the functional classification of gene sequences, common similarity-based methods often fall short of providing full and reliable functional information. Recently, the combination of comparative genomics with approaches in functional genomics has received considerable interest for gene function analysis, leveraging both gene expression based guilt-by-association methods and annotation efforts in closely related model organisms. Besides the identification of missing genes in pathways, these methods also typically enable the discovery of biological regulators (i.e., transcription factors or signaling genes). A previously built guilt-by-association method is MORPH, which was proven to be an efficient algorithm that performs particularly well in identifying and prioritizing missing genes in plant metabolic pathways. Here, we present MorphDB, a resource where MORPH-based candidate genes for large-scale functional annotations (Gene Ontology, MapMan bins) are integrated across multiple plant species. Besides a gene centric query utility, we present a comparative network approach that enables researchers to efficiently browse MORPH predictions across functional gene sets and species, facilitating efficient gene discovery and candidate gene prioritization. MorphDB is available at http://bioinformatics.psb.ugent.be/webtools/morphdb/morphDB/index/. We also provide a toolkit, named MORPH bulk (https://github.com/arzwa/morph-bulk), for running MORPH in bulk mode on novel data sets, enabling researchers to apply MORPH to their own species of interest." @default.
• W2792091229 created "2018-03-29" @default.
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• W2792091229 date "2018-03-19" @default.
• W2792091229 modified "2023-09-26" @default.
• W2792091229 title "MorphDB: Prioritizing Genes for Specialized Metabolism Pathways and Gene Ontology Categories in Plants" @default.
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• W2792091229 doi "https://doi.org/10.3389/fpls.2018.00352" @default.
• W2792091229 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5867296" @default.
• W2792091229 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29616063" @default.
• W2792091229 hasPublicationYear "2018" @default.
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