AIMC Topic: Computational Biology

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Comorbidity Scoring with Causal Disease Networks.

IEEE/ACM transactions on computational biology and bioinformatics
In recent years, there has been numerous studies constructing a disease network with diverse sources of data. Many researchers attempted to extend the usage of the disease network by employing machine learning algorithms on various problems such as p...

Prediction and characterization of human ageing-related proteins by using machine learning.

Scientific reports
Ageing has a huge impact on human health and economy, but its molecular basis - regulation and mechanism - is still poorly understood. By today, more than three hundred genes (almost all of them function as protein-coding genes) have been related to ...

Deep Learning and Its Applications in Biomedicine.

Genomics, proteomics & bioinformatics
Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the und...

Feasibility of an AI-Based Measure of the Hand Motions of Expert and Novice Surgeons.

Computational and mathematical methods in medicine
This study investigated whether parameters derived from hand motions of expert and novice surgeons accurately and objectively reflect laparoscopic surgical skill levels using an artificial intelligence system consisting of a three-layer chaos neural ...

Classifying dynamic transitions in high dimensional neural mass models: A random forest approach.

PLoS computational biology
Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhythms in health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understan...

Using Chou's general PseAAC to analyze the evolutionary relationship of receptor associated proteins (RAP) with various folding patterns of protein domains.

Journal of theoretical biology
The receptor-associated protein (RAP) is an inhibitor of endocytic receptors that belong to the lipoprotein receptor gene family. In this study, a computational approach was tried to find the evolutionarily related fold of the RAP proteins. Through t...

Simulations meet machine learning in structural biology.

Current opinion in structural biology
Classical molecular dynamics (MD) simulations will be able to reach sampling in the second timescale within five years, producing petabytes of simulation data at current force field accuracy. Notwithstanding this, MD will still be in the regime of lo...

Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires.

Frontiers in immunology
The adaptive immune system recognizes antigens an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in...

Statistical and machine learning approaches to predicting protein-ligand interactions.

Current opinion in structural biology
Data driven computational approaches to predicting protein-ligand binding are currently achieving unprecedented levels of accuracy on held-out test datasets. Up until now, however, this has not led to corresponding breakthroughs in our ability to des...

A critical review on the use of artificial neural networks in olive oil production, characterization and authentication.

Critical reviews in food science and nutrition
Artificial neural networks (ANN) are computationally based mathematical tools inspired by the fundamental cell of the nervous system, the neuron. ANN constitute a simplified artificial replica of the human brain consisting of parallel processing neur...