AIMC Topic: Computational Biology

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The whole is greater than its parts: ensembling improves protein contact prediction.

Scientific reports
The prediction of amino acid contacts from protein sequence is an important problem, as protein contacts are a vital step towards the prediction of folded protein structures. We propose that a powerful concept from deep learning, called ensembling, c...

A New Era of Neuro-Oncology Research Pioneered by Multi-Omics Analysis and Machine Learning.

Biomolecules
Although the incidence of central nervous system (CNS) cancers is not high, it significantly reduces a patient's quality of life and results in high mortality rates. A low incidence also means a low number of cases, which in turn means a low amount o...

Performance improvement for a 2D convolutional neural network by using SSC encoding on protein-protein interaction tasks.

BMC bioinformatics
BACKGROUND: The interactions of proteins are determined by their sequences and affect the regulation of the cell cycle, signal transduction and metabolism, which is of extraordinary significance to modern proteomics research. Despite advances in expe...

Artificial intelligence for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging.

EBioMedicine
BACKGROUND: artificial intelligence (AI) for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging (WSI) is lacking. We aim to establish an AI chronic rhinosinusitis evaluation platform 2.0 (AICEP 2.0) to obtain the proportion of infl...

Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data.

Scientific reports
A key challenge to gaining insight into complex systems is inferring nonlinear causal directional relations from observational time-series data. Specifically, estimating causal relationships between interacting components in large systems with only s...

Protein Complexes Detection Based on Semi-Supervised Network Embedding Model.

IEEE/ACM transactions on computational biology and bioinformatics
A protein complex is a group of associated polypeptide chains which plays essential roles in the biological process. Given a graph representing protein-protein interactions (PPI) network, it is critical but non-trivial to detect protein complexes, th...

Deep Convolutional and Recurrent Neural Networks for Cell Motility Discrimination and Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Cells in culture display diverse motility behaviors that may reflect differences in cell state and function, providing motivation to discriminate between different motility behaviors. Current methods to do so rely upon manual feature engineering. How...

Optimal Bayesian Transfer Learning for Count Data.

IEEE/ACM transactions on computational biology and bioinformatics
There is often a limited amount of omics data to design predictive models in biomedicine. Knowing that these omics data come from underlying processes that may share common pathways and disease mechanisms, it may be beneficial for designing a more ac...

A Framework for Automatic Burn Image Segmentation and Burn Depth Diagnosis Using Deep Learning.

Computational and mathematical methods in medicine
Burn is a common traumatic disease with high morbidity and mortality. The treatment of burns requires accurate and reliable diagnosis of burn wounds and burn depth, which can save lives in some cases. However, due to the complexity of burn wounds, th...

ncRFP: A Novel end-to-end Method for Non-Coding RNAs Family Prediction Based on Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Evidence has accumulated enough to prove non-coding RNAs (ncRNAs) play important roles in cellular biological processes and disease pathogenesis. High throughput techniques have produced a large number of ncRNAs whose function remains unknown. Since ...