AIMC Topic: Computational Biology

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Machine Learning Methods in Drug Discovery.

Molecules (Basel, Switzerland)
The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been use...

Early and accurate detection and diagnosis of heart disease using intelligent computational model.

Scientific reports
Heart disease is a fatal human disease, rapidly increases globally in both developed and undeveloped countries and consequently, causes death. Normally, in this disease, the heart fails to supply a sufficient amount of blood to other parts of the bod...

Predicting antibody affinity changes upon mutations by combining multiple predictors.

Scientific reports
Antibodies are proteins working in our immune system with high affinity and specificity for target antigens, making them excellent tools for both biotherapeutic and bioengineering applications. The prediction of antibody affinity changes upon mutatio...

COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images.

Scientific reports
The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population. A critical step in the fight against COVID-19 is effective screening of infected patients, with one of the ...

Deep learning predicts short non-coding RNA functions from only raw sequence data.

PLoS computational biology
Small non-coding RNAs (ncRNAs) are short non-coding sequences involved in gene regulation in many biological processes and diseases. The lack of a complete comprehension of their biological functionality, especially in a genome-wide scenario, has dem...

Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values.

EBioMedicine
BACKGROUND: Sepsis is a heterogenous syndrome and individualized management strategy is the key to successful treatment. Genome wide expression profiling has been utilized for identifying subclasses of sepsis, but the clinical utility of these subcla...

Pathway information extracted from 25 years of pathway figures.

Genome biology
Thousands of pathway diagrams are published each year as static figures inaccessible to computational queries and analyses. Using a combination of machine learning, optical character recognition, and manual curation, we identified 64,643 pathway figu...

Cancer classification based on chromatin accessibility profiles with deep adversarial learning model.

PLoS computational biology
Given the complexity and diversity of the cancer genomics profiles, it is challenging to identify distinct clusters from different cancer types. Numerous analyses have been conducted for this propose. Still, the methods they used always do not direct...

Deep learning approach for predicting functional Z-DNA regions using omics data.

Scientific reports
Computational methods to predict Z-DNA regions are in high demand to understand the functional role of Z-DNA. The previous state-of-the-art method Z-Hunt is based on statistical mechanical and energy considerations about B- to Z-DNA transition using ...