AIMC Topic: Computational Biology

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Survey of Machine Learning Techniques in Drug Discovery.

Current drug metabolism
BACKGROUND: Drug discovery, which is the process of discovering new candidate medications, is very important for pharmaceutical industries. At its current stage, discovering new drugs is still a very expensive and time-consuming process, requiring Ph...

Prediction of human-Bacillus anthracis protein-protein interactions using multi-layer neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Triplet amino acids have successfully been included in feature selection to predict human-HPV protein-protein interactions (PPI). The utility of supervised learning methods is curtailed due to experimental data not being available in suff...

SpliceRover: interpretable convolutional neural networks for improved splice site prediction.

Bioinformatics (Oxford, England)
MOTIVATION: During the last decade, improvements in high-throughput sequencing have generated a wealth of genomic data. Functionally interpreting these sequences and finding the biological signals that are hallmarks of gene function and regulation is...

Combined multivariate analysis and machine learning reveals a predictive module of metabolic stress response in Arabidopsis thaliana.

Molecular omics
Abiotic stress exposure of plants induces metabolic reprogramming which is tightly regulated by signalling cascades connecting transcriptional with translational and metabolic regulation. Complexity of such interconnected metabolic networks impedes t...

Cancers classification based on deep neural networks and emotional learning approach.

IET systems biology
In the present era, enormous factors contribute to causing cancer. So cancer classification cannot rely only on doctor's thoughts. As a result, intelligent algorithms concerning doctor's help are inevitable. Therefore, the authors are motivated to su...

Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Accurate prediction of a protein contact map depends greatly on capturing as much contextual information as possible from surrounding residues for a target residue pair. Recently, ultra-deep residual convolutional networks were found to b...

Deep convolutional networks for quality assessment of protein folds.

Bioinformatics (Oxford, England)
MOTIVATION: The computational prediction of a protein structure from its sequence generally relies on a method to assess the quality of protein models. Most assessment methods rank candidate models using heavily engineered structural features, define...

Transfer learning for biomedical named entity recognition with neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/protei...

Hercules: a profile HMM-based hybrid error correction algorithm for long reads.

Nucleic acids research
Choosing whether to use second or third generation sequencing platforms can lead to trade-offs between accuracy and read length. Several types of studies require long and accurate reads. In such cases researchers often combine both technologies and t...