AIMC Topic: Computational Biology

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Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

PLoS computational biology
MOTIVATION: Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predict...

PaPrBaG: A machine learning approach for the detection of novel pathogens from NGS data.

Scientific reports
The reliable detection of novel bacterial pathogens from next-generation sequencing data is a key challenge for microbial diagnostics. Current computational tools usually rely on sequence similarity and often fail to detect novel species when closely...

An Overview of data science uses in bioimage informatics.

Methods (San Diego, Calif.)
This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object...

Deep Learning for Health Informatics.

IEEE journal of biomedical and health informatics
With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on machine learn...

Machine-learned cluster identification in high-dimensional data.

Journal of biomedical informatics
BACKGROUND: High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the...

An improved method for functional similarity analysis of genes based on Gene Ontology.

BMC systems biology
BACKGROUND: Measures of gene functional similarity are essential tools for gene clustering, gene function prediction, evaluation of protein-protein interaction, disease gene prioritization and other applications. In recent years, many gene functional...

Improved protein-protein interactions prediction via weighted sparse representation model combining continuous wavelet descriptor and PseAA composition.

BMC systems biology
BACKGROUND: Protein-protein interactions (PPIs) are essential to most biological processes. Since bioscience has entered into the era of genome and proteome, there is a growing demand for the knowledge about PPI network. High-throughput biological te...

Pretata: predicting TATA binding proteins with novel features and dimensionality reduction strategy.

BMC systems biology
BACKGROUND: It is necessary and essential to discovery protein function from the novel primary sequences. Wet lab experimental procedures are not only time-consuming, but also costly, so predicting protein structure and function reliably based only o...

Interspecies gene function prediction using semantic similarity.

BMC systems biology
BACKGROUND: Gene Ontology (GO) is a collaborative project that maintains and develops controlled vocabulary (or terms) to describe the molecular function, biological roles and cellular location of gene products in a hierarchical ontology. GO also pro...

DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations.

BMC bioinformatics
BACKGROUND: With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer...