AIMC Topic: Computational Biology

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Developing new VOmax prediction models from maximal, submaximal and questionnaire variables using support vector machines combined with feature selection.

Computers in biology and medicine Oct 20, 2016
Maximal oxygen uptake (VOmax) is an essential part of health and physical fitness, and refers to the highest rate of oxygen consumption an individual can attain during exhaustive exercise. In this study, for the first time in the literature, we combi...
Models, Cardiovascular Humans Surveys and Questionnaires Computational Biology Regression Analysis Oxygen Consumption Support Vector Machine Models, Statistical
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Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes.

BMC genomics Oct 18, 2016
BACKGROUND: Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheim...
Protein Interaction Mapping Genetic Association Studies Computational Biology Alzheimer Disease Datasets as Topic Molecular Sequence Annotation Gene Ontology Reproducibility of Results Gene Expression Profiling Genetic Predisposition to Disease Humans Machine Learning
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Introducing the Big Knowledge to Use (BK2U) challenge.

Annals of the New York Academy of Sciences Oct 17, 2016
The purpose of the Big Data to Knowledge initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK),...
Image Processing, Computer-Assisted Computational Biology Models, Neurological Humans Animals Knowledge Bases Data Mining Image Interpretation, Computer-Assisted Systematized Nomenclature of Medicine Pharmaceutical Preparations Drug Interactions Translational Research, Biomedical Terminology as Topic Intracranial Hemorrhages Decision Making, Computer-Assisted
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RAFP-Pred: Robust Prediction of Antifreeze Proteins Using Localized Analysis of n-Peptide Compositions.

IEEE/ACM transactions on computational biology and bioinformatics Oct 13, 2016
In extreme cold weather, living organisms produce Antifreeze Proteins (AFPs) to counter the otherwise lethal intracellular formation of ice. Structures and sequences of various AFPs exhibit a high degree of heterogeneity, consequently the prediction ...
Sequence Analysis, Protein Antifreeze Proteins Computational Biology Databases, Protein Dipeptides Machine Learning Algorithms ROC Curve
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Predicting the Organelle Location of Noncoding RNAs Using Pseudo Nucleotide Compositions.

Interdisciplinary sciences, computational life sciences Oct 13, 2016
Noncoding RNAs (ncRNAs) are implicated in various biological processes. Recent findings have demonstrated that the function of ncRNAs correlates with their provenance. Therefore, the recognition of ncRNAs from different organelle genomes will be help...
RNA, Untranslated Support Vector Machine Algorithms Nucleotides Computational Biology
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Predicting Protein-DNA Binding Residues by Weightedly Combining Sequence-Based Features and Boosting Multiple SVMs.

IEEE/ACM transactions on computational biology and bioinformatics Oct 11, 2016
Protein-DNA interactions are ubiquitous in a wide variety of biological processes. Correctly locating DNA-binding residues solely from protein sequences is an important but challenging task for protein function annotations and drug discovery, especia...
Databases, Protein Computational Biology Support Vector Machine DNA-Binding Proteins Models, Statistical Amino Acid Sequence
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Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2016
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 ...
Transcriptome Computational Biology Models, Genetic Machine Learning Gene Expression Profiling Molecular Sequence Annotation Gene Ontology Genes Arabidopsis Databases, Genetic Cluster Analysis Saccharomyces cerevisiae
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HEMEsPred: Structure-Based Ligand-Specific Heme Binding Residues Prediction by Using Fast-Adaptive Ensemble Learning Scheme.

IEEE/ACM transactions on computational biology and bioinformatics Oct 4, 2016
Heme is an essential biomolecule that widely exists in numerous extant organisms. Accurately identifying heme binding residues (HEMEs) is of great importance in disease progression and drug development. In this study, a novel predictor named HEMEsPre...
Machine Learning Software Algorithms Protein Binding Computational Biology Databases, Protein Heme Models, Molecular Binding Sites Protein Structure, Secondary
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Improving information retrieval in functional analysis.

Computers in biology and medicine Sep 24, 2016
Transcriptome analysis is essential to understand the mechanisms regulating key biological processes and functions. The first step usually consists of identifying candidate genes; to find out which pathways are affected by those genes, however, funct...
Computational Biology Information Storage and Retrieval Humans Female Artificial Intelligence Algorithms Breast Neoplasms Gene Expression Profiling
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Evidence-based selection of training compounds for use in the mechanism-based integrated prediction of drug-induced liver injury in man.

Archives of toxicology Sep 22, 2016
The current test systems employed by pharmaceutical industry are poorly predictive for drug-induced liver injury (DILI). The 'MIP-DILI' project addresses this situation by the development of innovative preclinical test systems which are both mechanis...
Molecular Structure Humans Lysosomes Oxidative Stress Artificial Intelligence Expert Systems Chemical and Drug Induced Liver Injury Models, Biological Computational Biology Animals Drugs, Investigational Evidence-Based Medicine Hepatobiliary Elimination Liver Severity of Illness Index Mitochondria, Liver Adaptive Immunity
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