Tissue-spEcific mrNa iSoform functIOnal Networks (TENSION) Collection
Version 4 2019-01-09, 15:39
Version 3 2018-10-29, 19:55
Version 2 2018-10-25, 21:15
Version 1 2018-10-23, 21:33
Posted on 2019-01-09 - 15:39 authored by Gaurav Kandoi
The files for this project have been split into three separate download packages:
- Predictions
- Predictions
- Scripts
- Datasets
Each package has a copy of the readme file which covers all three packages.
Alternative Splicing produces multiple
mRNA isoforms of a gene which have important diverse roles such as regulation
of gene expression, human heritable diseases, and response to environmental
stresses. However, very little has been done to assign functions at the mRNA
isoform level. Functional networks, where the interactions are quantified by
their probability of being involved in the same biological process are
typically generated at the gene level. We use a diverse array of tissue-specific
RNA-seq datasets and sequence information to train random forest models for
predicting the functional networks following a leave-one-tissue-out strategy.
Since there is no mRNA isoform-level gold standard, we use single isoform genes
co-annotated to Gene Ontology biological process annotations, Kyoto
Encyclopedia of Genes and Genomes pathways, BioCyc pathways and protein-protein
interactions as functionally related (positive pair). To generate the
non-functional pairs (negative pair), we use the Gene Ontology annotations
tagged with “NOT” qualifier. We describe 17 Tissue-spEcific mrNa iSoform
functIOnal Networks (TENSION) in addition to an organism level reference
functional network for mouse. We validate our predictions by comparing its
performance with previous methods, randomized positive and negative class
labels, updated Gene Ontology annotations, and by literature evidence.
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Dickerson, Julie; Kandoi, Gaurav (2018). Tissue-spEcific mrNa iSoform functIOnal Networks (TENSION) Collection. Iowa State University. Collection. https://doi.org/10.25380/iastate.c.4275191.v4
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FUNDING
ABI Innovation: Model-based Alternative Splicing Analysis Across Expression Platforms
Directorate for Biological Sciences
XSEDE 2.0: Integrating, Enabling and Enhancing National Cyberinfrastructure with Expanding Community Involvement
Directorate for Computer & Information Science & Engineering
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AUTHORS (2)
CATEGORIES
- Animal cell and molecular biology
- Animal structure and function
- Bioinformatics and computational biology not elsewhere classified
- Gene expression (incl. microarray and other genome-wide approaches)
- Genetics not elsewhere classified
- Genome structure and regulation
- Genomics
- Plant cell and molecular biology
- Proteomics and intermolecular interactions (excl. medical proteomics)
- Biomolecular modelling and design
- Proteins and peptides
- Knowledge representation and reasoning
KEYWORDS
alternative splicingmRNA Isoform Networkstissue-specificMouseRandom ForestBiological NetworksMachine LearningTENSIONTranscricpt-level NetworksGene OntologyNetwork PredictionFunctional Networkssequence featuresRNA-SeqTissue Expression ProfileAnimal Cell and Molecular BiologyAnimal Structure and FunctionBioinformaticsComputational BiologyGene Expression (incl. Microarray and other genome-wide approaches)GeneticsGenome Structure and RegulationGenomicsMolecular BiologyProteomics and Intermolecular Interactions (excl. Medical Proteomics)Biomolecular Modelling and DesignProteins and PeptidesKnowledge Representation and Machine Learning