Studying the Cohesion Evolution of Genes Related to Chronic Lymphocytic Leukemia Using Semantic Similarity in Gene Ontology and Self-Organizing Maps

A significant body of work on biomedical text mining is aimed at uncovering meaningful associations between biological entities, including genes. This has the potential to offer new insights for re ...

[1]  S. Schuster Next-generation sequencing transforms today's biology , 2008, Nature Methods.

[2]  G. Fabbri,et al.  The molecular pathogenesis of chronic lymphocytic leukaemia , 2016, Nature Reviews Cancer.

[3]  Philip S. Yu,et al.  A new method to measure the semantic similarity of GO terms , 2007, Bioinform..

[4]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[5]  David Sánchez,et al.  Ontology-based semantic similarity: A new feature-based approach , 2012, Expert Syst. Appl..

[6]  Martin Chodorow,et al.  Combining local context and wordnet similarity for word sense identification , 1998 .

[7]  T. Jenssen,et al.  A literature network of human genes for high-throughput analysis of gene expression , 2001, Nature Genetics.

[8]  N. Chiorazzi,et al.  B cell receptor signaling in chronic lymphocytic leukemia. , 2013, Trends in immunology.

[9]  Mário J. Silva,et al.  Measuring semantic similarity between Gene Ontology terms , 2007, Data Knowl. Eng..

[10]  Michael W. Berry,et al.  Gene clustering by Latent Semantic Indexing of MEDLINE abstracts , 2005, Bioinform..

[11]  Yiannis Kompatsiaris,et al.  Monitoring term drift based on semantic consistency in an evolving vector field , 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

[12]  J. Tenenbaum,et al.  A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.

[13]  Elizabeth Chang,et al.  A Hybrid Concept Similarity Measure Model for Ontology Environment , 2009, OTM Workshops.

[14]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[15]  Carole A. Goble,et al.  Semantic Similarity Measures as Tools for Exploring the Gene Ontology , 2002, Pacific Symposium on Biocomputing.

[16]  International Human Genome Sequencing Consortium Finishing the euchromatic sequence of the human genome , 2004 .

[17]  Giorgio Valentini,et al.  GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology , 2014, Bioinform..

[18]  T. Jenssen,et al.  A literature network of human genes for high-throughput analysis of gene expression , 2001 .

[19]  Martha Palmer,et al.  Verb Semantics and Lexical Selection , 1994, ACL.

[20]  Peter Wittek,et al.  A Vector Field Approach to Lexical Semantics , 2014, QI.

[21]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .

[22]  Jin Zhao,et al.  GenCLiP: a software program for clustering gene lists by literature profiling and constructing gene co-occurrence networks related to custom keywords , 2008, BMC Bioinformatics.

[23]  Philip S. Yu,et al.  Measure the Semantic Similarity of GO Terms Using Aggregate Information Content , 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[24]  Wittek,et al.  somoclu : An Efficient Parallel Library for Self-Organizing Maps , 2016 .

[25]  Philip Resnik,et al.  Using Information Content to Evaluate Semantic Similarity in a Taxonomy , 1995, IJCAI.

[26]  Christiane Fellbaum,et al.  Combining Local Context and Wordnet Similarity for Word Sense Identification , 1998 .

[27]  Yibo Wu,et al.  GOSemSim: an R package for measuring semantic similarity among GO terms and gene products , 2010, Bioinform..

[28]  David W. Conrath,et al.  Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy , 1997, ROCLING/IJCLCLP.

[29]  Dennis M. Wilkinson,et al.  A method for finding communities of related genes , 2004, Proceedings of the National Academy of Sciences of the United States of America.