Information theory applied to the sparse gene ontology annotation network to predict novel gene function

Tang, Ying; Sam, Lee; Lǐ, Jiànróng; Friedman, Carol; Lussier, Yves A.

doi:10.1093/bioinformatics/btm195

Cited by 150 publications

(141 citation statements)

References 55 publications

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“…The predicted gene/protein function in the NCBI database was searched against InterPro using the available online bioinformatics tool (http://www. uniprot.org) and determined according to Tao et al (2007) and Chitale et al (2009).…”

Section: Data Mining and Annotation Of Putative Tdfsmentioning

confidence: 99%

Identification of predicted genes expressed differentially in pituitary gland tissue of young growing bulls revealed by cDNA-AFLP technique

Pareek¹,

Michno²,

Smoczyński³

et al. 2013

CZECH J ANIM SCI

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Differentially expressed transcript derived fragments (TDFs) of bovine pituitary gland tissue at different developmental ages of Limousine and Hereford bulls were identified by cDNA-AFLP technique. Study revealed comparatively higher differentially expressed transcripts in 6-month Limousine bulls and 12-month Hereford bulls. The BLASTn/p analysis identified 3 and 21 predicted genes which gave significant e-values for Limousine and Hereford respectively, in assembled Bos taurus genome. The identified predicted genes expressed in bovine pituitary gland showed their mapped positions on bovine chromosomes: BTA2, 3, 5, 8, 9, 11, 12,[15][16][17][18][19][20][21][22][23] 26, and 28, respectively. Results based on TDF annotation identified 10 sequences that have BLAST hits to known annotated bovine genes and 14 sequences to unannotated contig regions in the latest gene Ensembl database Btau_4.0. Two breed specific predicted target genes were validated by qRT-PCR. Within and between breeds, qRT-PCR results revealed highly significant differences in the expression levels of bovine euchromatic histone-lysine N-methyltransferase 1 (EHMT1) and NCK adaptor protein 2 (NCK2) predicted genes. Obtained results conclude that cDNA-AFLP is a reliable technique for studying within breed age dependent gene expression patterns.

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Section: Data Mining and Annotation Of Putative Tdfsmentioning

confidence: 99%

Identification of predicted genes expressed differentially in pituitary gland tissue of young growing bulls revealed by cDNA-AFLP technique

Pareek¹,

Michno²,

Smoczyński³

et al. 2013

CZECH J ANIM SCI

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“…Guo et al compared a number of network-based and information content-based semantic similarity methods in distinguishing true and false human PPIs, and concluded that the average (AVG) method by Resnik performed best in AUROC analysis [55][56][57][58]. Xu et al compared the AVG and maximum (MAX) methods by Resnik to a number of semantic similarity methods specifically developed for GO, and concluded that the MAX method by Resnik outperforms others when considering the three ontologies of GO either individually or together [55,[59][60][61][62]. More recently, our group developed the Topological Clustering Semantic Similarity (TCSS) method, which uses a novel normalization technique before computing similarity [63].…”

Section: Cellular Location Biological Process Molecular Functionmentioning

confidence: 99%

Domain‐mediated protein interaction prediction: From genome to network

et al. 2012

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a b s t r a c tProtein-protein interactions (PPIs), involved in many biological processes such as cellular signaling, are ultimately encoded in the genome. Solving the problem of predicting protein interactions from the genome sequence will lead to increased understanding of complex networks, evolution and human disease. We can learn the relationship between genomes and networks by focusing on an easily approachable subset of high-resolution protein interactions that are mediated by peptide recognition modules (PRMs) such as PDZ, WW and SH3 domains. This review focuses on computational prediction and analysis of PRM-mediated networks and discusses sequence-and structure-based interaction predictors, techniques and datasets for identifying physiologically relevant PPIs, and interpreting high-resolution interaction networks in the context of evolution and human disease.

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“…Finally, we evaluate the prediction accuracy using two types of background knowledge -domain and raw knowledge, as opposed to only domain knowledge in their case. Additional related work includes [15], where the authors use a threshold of lowest semantic similarity value to find best-matching term pairs with the goal of predicting molecular functions of genes in Gene Ontology (GO) [16] annotations. Similar to our work, the authors tailor the semantic similarity measures according to fit the structure of GO and their application requirements.…”

Section: Related Workmentioning

confidence: 99%

Semantic Similarity-Driven Decision Support in the Skeletal Dysplasia Domain

Paul

Groza

Zankl

et al. 2012

The Semantic Web – ISWC 2012

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Abstract. Biomedical ontologies have become a mainstream topic in medical research. They represent important sources of evolved knowledge that may be automatically integrated in decision support methods. Grounding clinical and radiographic findings in concepts defined by a biomedical ontology, e.g., the Human Phenotype Ontology, enables us to compute semantic similarity between them. In this paper, we focus on using such similarity measures to predict disorders on undiagnosed patient cases in the bone dysplasia domain. Different methods for computing the semantic similarity have been implemented. All methods have been evaluated based on their support in achieving a higher prediction accuracy. The outcome of this research enables us to understand the feasibility of developing decision support methods based on ontology-driven semantic similarity in the skeletal dysplasia domain.

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Information theory applied to the sparse gene ontology annotation network to predict novel gene function

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 150 publications

References 55 publications

Identification of predicted genes expressed differentially in pituitary gland tissue of young growing bulls revealed by cDNA-AFLP technique

Identification of predicted genes expressed differentially in pituitary gland tissue of young growing bulls revealed by cDNA-AFLP technique

Domain‐mediated protein interaction prediction: From genome to network

Semantic Similarity-Driven Decision Support in the Skeletal Dysplasia Domain

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