AIMC Topic: Databases, Genetic

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Two-way learning with one-way supervision for gene expression data.

BMC bioinformatics
BACKGROUND: A family of parsimonious Gaussian mixture models for the biclustering of gene expression data is introduced. Biclustering is accommodated by adopting a mixture of factor analyzers model with a binary, row-stochastic factor loadings matrix...

A novel hierarchical selective ensemble classifier with bioinformatics application.

Artificial intelligence in medicine
Selective ensemble learning is a technique that selects a subset of diverse and accurate basic models in order to generate stronger generalization ability. In this paper, we proposed a novel learning algorithm that is based on parallel optimization a...

Identification of miRNA-mRNA Modules in Colorectal Cancer Using Rough Hypercuboid Based Supervised Clustering.

Scientific reports
Differences in the expression profiles of miRNAs and mRNAs have been reported in colorectal cancer. Nevertheless, information on important miRNA-mRNA regulatory modules in colorectal cancer is still lacking. In this regard, this study presents an app...

V-ELMpiRNAPred: Identification of human piRNAs by the voting-based extreme learning machine (V-ELM) with a new hybrid feature.

Journal of bioinformatics and computational biology
Piwi-interacting RNAs (piRNAs) were recently discovered as endogenous small noncoding RNAs. Some recent research suggests that piRNAs may play an important role in cancer. So the precise identification of human piRNAs is a significant work. In this p...

Interspecies gene function prediction using semantic similarity.

BMC systems biology
BACKGROUND: Gene Ontology (GO) is a collaborative project that maintains and develops controlled vocabulary (or terms) to describe the molecular function, biological roles and cellular location of gene products in a hierarchical ontology. GO also pro...

Ensemble Clustering Classification compete SVM and One-Class classifiers applied on plant microRNAs Data.

Journal of integrative bioinformatics
The performance of many learning and data mining algorithms depends critically on suitable metrics to assess efficiency over the input space. Learning a suitable metric from examples may, therefore, be the key to successful application of these algor...

Introducing a Stable Bootstrap Validation Framework for Reliable Genomic Signature Extraction.

IEEE/ACM transactions on computational biology and bioinformatics
The application of machine learning methods for the identification of candidate genes responsible for phenotypes of interest, such as cancer, is a major challenge in the field of bioinformatics. These lists of genes are often called genomic signature...

Expansion of the Gene Ontology knowledgebase and resources.

Nucleic acids research
The Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. As such, it is extensively used by the biomedical research community for the analysis of -omics and related data. Our conti...

Analysis of Important Gene Ontology Terms and Biological Pathways Related to Pancreatic Cancer.

BioMed research international
Pancreatic cancer is a serious disease that results in more than thirty thousand deaths around the world per year. To design effective treatments, many investigators have devoted themselves to the study of biological processes and mechanisms underlyi...

Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics
Characterizing genes with semantic information is an important process regarding the description of gene products. In spite that complete genomes of many organisms have been already sequenced, the biological functions of all of their genes are still ...