AIMC Topic: Computational Biology

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Sequential Integration of Fuzzy Clustering and Expectation Maximization for Transcription Factor Binding Site Identification.

Journal of computational biology : a journal of computational molecular cell biology
The identification of transcription factor binding sites (TFBSs) is a problem for which computational methods offer great hope. Thus far, the expectation maximization (EM) technique has been successfully utilized in finding TFBSs in DNA sequences, bu...

Identification of synthetic lethality based on a functional network by using machine learning algorithms.

Journal of cellular biochemistry
Synthetic lethality is the synthesis of mutations leading to cell death. Tumor-specific synthetic lethality has been targeted in research to improve cancer therapy. With the advances of techniques in molecular biology, such as RNAi and CRISPR/Cas9 ge...

Exploiting MEDLINE for gene molecular function prediction via NMF based multi-label classification.

Journal of biomedical informatics
Gene ontology (GO) provides a representation of terms and categories used to describe genes and their molecular functions, cellular components and biological processes. GO has been the standard for describing the functions of specific genes in differ...

iRNA-2OM: A Sequence-Based Predictor for Identifying 2'-O-Methylation Sites in Homo sapiens.

Journal of computational biology : a journal of computational molecular cell biology
2'-O-methylation plays an important biological role in gene expression. Owing to the explosive increase in genomic sequencing data, it is necessary to develop a method for quickly and efficiently identifying whether a sequence contains the 2'-O-methy...

Artificial Fish Swarm Optimization Based Method to Identify Essential Proteins.

IEEE/ACM transactions on computational biology and bioinformatics
It is well known that essential proteins play an extremely important role in controlling cellular activities in living organisms. Identifying essential proteins from protein protein interaction (PPI) networks is conducive to the understanding of cell...

Uncertainty, imprecision, and many-valued logics in protein bioinformatics.

Mathematical biosciences
Understanding proteins, their structures, functions, mutual interactions, activity in cellular reactions, interactions with drugs, and expression in body cells is a key to efficient medical diagnosis, drug production, and treatment of patients. Machi...

Gene Ontology Enrichment Improves Performances of Functional Similarity of Genes.

Scientific reports
There exists a plethora of measures to evaluate functional similarity (FS) between genes, which is a widely used in many bioinformatics applications including detecting molecular pathways, identifying co-expressed genes, predicting protein-protein in...

Integration of Gene Expression Profile Data to Screen and Verify Hub Genes Involved in Osteoarthritis.

BioMed research international
Osteoarthritis (OA) is one of the most common diseases worldwide, but the pathogenic genes and pathways are largely unclear. The aim of this study was to screen and verify hub genes involved in OA and explore potential molecular mechanisms. The expre...

A New Method for Recognizing Cytokines Based on Feature Combination and a Support Vector Machine Classifier.

Molecules (Basel, Switzerland)
Research on cytokine recognition is of great significance in the medical field due to the fact cytokines benefit the diagnosis and treatment of diseases, but the current methods for cytokine recognition have many shortcomings, such as low sensitivity...

Identifying Phage Virion Proteins by Using Two-Step Feature Selection Methods.

Molecules (Basel, Switzerland)
Accurate identification of phage virion protein is not only a key step for understanding the function of the phage virion protein but also helpful for further understanding the lysis mechanism of the bacterial cell. Since traditional experimental met...