AIMC Topic: Computational Biology

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SBOannotator: a Python tool for the automated assignment of systems biology ontology terms.

Bioinformatics (Oxford, England)
MOTIVATION: The number and size of computational models in biology have drastically increased over the past years and continue to grow. Modeled networks are becoming more complex, and reconstructing them from the beginning in an exchangeable and repr...

[Advances in machine learning for predicting protein functions].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Proteins play a variety of functional roles in cellular activities and are indispensable for life. Understanding the functions of proteins is crucial in many fields such as medicine and drug development. In addition, the application of enzymes in gre...

Report on the FEBS-IUBMB-ENABLE 1st International Molecular Biosciences PhD and Postdoc Conference.

FEBS open bio
The FEBS-IUBMB-ENABLE 1st International Molecular Biosciences PhD and Postdoc Conference was held in Seville, Spain, from the 16-18th of November 2022. Nearly 300 participants from all over the globe were welcomed by the host institution, the Institu...

A Review on Deep Learning-driven Drug Discovery: Strategies, Tools and Applications.

Current pharmaceutical design
It takes an average of 10-15 years to uncover and develop a new drug, and the process is incredibly time-consuming, expensive, difficult, and ineffective. In recent years the dramatic changes in the field of artificial intelligence (AI) have helped t...

Inter-domain distance prediction based on deep learning for domain assembly.

Briefings in bioinformatics
AlphaFold2 achieved a breakthrough in protein structure prediction through the end-to-end deep learning method, which can predict nearly all single-domain proteins at experimental resolution. However, the prediction accuracy of full-chain proteins is...

Predicting the pathogenicity of missense variants using features derived from AlphaFold2.

Bioinformatics (Oxford, England)
MOTIVATION: Missense variants are a frequent class of variation within the coding genome, and some of them cause Mendelian diseases. Despite advances in computational prediction, classifying missense variants into pathogenic or benign remains a major...

MARSY: a multitask deep-learning framework for prediction of drug combination synergy scores.

Bioinformatics (Oxford, England)
MOTIVATION: Combination therapies have emerged as a treatment strategy for cancers to reduce the probability of drug resistance and to improve outcomes. Large databases curating the results of many drug screening studies on preclinical cancer cell li...

Harnessing Deep Learning for Omics in an Era of COVID-19.

Omics : a journal of integrative biology
Omics data are multidimensional, heterogeneous, and high throughput. Robust computational methods and machine learning (ML)-based models offer new prospects to accelerate the data-to-knowledge trajectory. Deep learning (DL) is a powerful subset of ML...

Machine learning on protein-protein interaction prediction: models, challenges and trends.

Briefings in bioinformatics
Protein-protein interactions (PPIs) carry out the cellular processes of all living organisms. Experimental methods for PPI detection suffer from high cost and false-positive rate, hence efficient computational methods are highly desirable for facilit...

Collaborative deep learning improves disease-related circRNA prediction based on multi-source functional information.

Briefings in bioinformatics
Emerging studies have shown that circular RNAs (circRNAs) are involved in a variety of biological processes and play a key role in disease diagnosing, treating and inferring. Although many methods, including traditional machine learning and deep lear...