AIMC Topic: Computational Biology

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Identification of hormone binding proteins based on machine learning methods.

Mathematical biosciences and engineering : MBE
The soluble carrier hormone binding protein (HBP) plays an important role in the growth of human and other animals. HBP can also selectively and non-covalently interact with hormone. Therefore, accurate identification of HBP is an important prerequis...

Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer.

Briefings in bioinformatics
Breast cancer prognosis and administration of therapies are aided by knowledge of hormonal and HER2 receptor status. Breast cancer lacking estrogen receptors, progesterone receptors and HER2 receptors are difficult to treat. Regarding large data repo...

miES: predicting the essentiality of miRNAs with machine learning and sequence features.

Bioinformatics (Oxford, England)
MOTIVATION: MicroRNAs (miRNAs) are one class of small noncoding RNA molecules, which regulate gene expression at the post-transcriptional level and play important roles in health and disease. To dissect the critical miRNAs in miRNAome, it is needed t...

[Machine Learning Applications in Cancer Genome Medicine].

Gan to kagaku ryoho. Cancer & chemotherapy
Practical cancer genome medicine requires large-scale data analysis for many types of biological data such as cancer driver mutations, aberrantly methylated regions, gene expression also biological knowledge from literature. Machine learning algorith...

MCO: towards an ontology and unified vocabulary for a framework-based annotation of microbial growth conditions.

Bioinformatics (Oxford, England)
MOTIVATION: A major component in increasing our understanding of the biology of an organism is the mapping of its genotypic potential into its phenotypic expression profiles. This mapping is executed by the machinery of gene regulation, which is esse...

On discrete time Beverton-Holt population model with fuzzy environment.

Mathematical biosciences and engineering : MBE
In this work, dynamical behaviors of discrete time Beverton-Holt population model with fuzzy parameters are studied. It provides a flexible model to fit population data. For three different fuzzy parameters and fuzzy initial conditions, according to ...

4mCPred: machine learning methods for DNA N4-methylcytosine sites prediction.

Bioinformatics (Oxford, England)
MOTIVATION: N4-methylcytosine (4mC), an important epigenetic modification formed by the action of specific methyltransferases, plays an essential role in DNA repair, expression and replication. The accurate identification of 4mC sites aids in-depth r...

Deep learning in omics: a survey and guideline.

Briefings in functional genomics
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fortunately,...