AIMC Topic: Models, Genetic

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Prediction of MicroRNA-Disease Associations Based on Social Network Analysis Methods.

BioMed research international
MicroRNAs constitute an important class of noncoding, single-stranded, ~22 nucleotide long RNA molecules encoded by endogenous genes. They play an important role in regulating gene transcription and the regulation of normal development. MicroRNAs can...

SFM: A novel sequence-based fusion method for disease genes identification and prioritization.

Journal of theoretical biology
The identification of disease genes from human genome is of great importance to improve diagnosis and treatment of disease. Several machine learning methods have been introduced to identify disease genes. However, these methods mostly differ in the p...

Discrimination of driver and passenger mutations in epidermal growth factor receptor in cancer.

Mutation research
Cancer is one of the most life-threatening diseases and mutations in several genes are the vital cause in tumorigenesis. Protein kinases play essential roles in cancer progression and specifically, epidermal growth factor receptor (EGFR) is an import...

Genome Modeling System: A Knowledge Management Platform for Genomics.

PLoS computational biology
In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled...

Machine learning applications in genetics and genomics.

Nature reviews. Genetics
The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets. Here, we provide an overview of machine learning ap...

Multiscale Modeling of Gene-Behavior Associations in an Artificial Neural Network Model of Cognitive Development.

Cognitive science
In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively...

State of the art of fuzzy methods for gene regulatory networks inference.

TheScientificWorldJournal
To address one of the most challenging issues at the cellular level, this paper surveys the fuzzy methods used in gene regulatory networks (GRNs) inference. GRNs represent causal relationships between genes that have a direct influence, trough protei...

A robust computational technique for model order reduction of two-time-scale discrete systems via genetic algorithms.

Computational intelligence and neuroscience
A robust computational technique for model order reduction (MOR) of multi-time-scale discrete systems (single input single output (SISO) and multi-input multioutput (MIMO)) is presented in this paper. This work is motivated by the singular perturbati...

Aber-OWL: a framework for ontology-based data access in biology.

BMC bioinformatics
BACKGROUND: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within t...

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

BMC genomics
BACKGROUND: Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large ...