Computational Methods for Protein Structures

Computational methods employing machine learning algorithms are powerful tools that can be used to predict the effect of mutations on protein structure. This is important in neurodegenerative disorders, where some mutations can cause the formation of toxic protein aggregations. This feed follows the latests insights into the relationships between mutation and protein structure leading to better understanding of disease.

November 10, 2020
Open Access

FireProtDB: database of manually curated protein stability data.

Nucleic Acids Research
Jan StouracDavid Bednar
November 3, 2020
Open Access

RNA inter-nucleotide 3D closeness prediction by deep residual neural networks

Bioinformatics
Saisai SunJianyi Yang
May 18, 2020
Open Access

Biased Gene Conversion Constrains Adaptation in Arabidopsis thaliana

Genetics
Tuomas Hämälä, Peter Tiffin
August 23, 2020
Open Access

Nicotinic Cholinergic System and COVID-19: In Silico Identification of an Interaction between SARS-CoV-2 and Nicotinic Receptors with Potential Therapeutic Targeting Implications

International Journal of Molecular Sciences
Konstantinos FarsalinosKonstantinos Poulas
December 18, 2020
Preprint
Open Access

Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods

ResearchSquare
Farshid ShirafkanJavad Zahiri
January 14, 2021
Preprint
Open Access

Improving integrative 3D modeling into low- to medium- resolution EM structures with evolutionary couplings

BioRxiv : the Preprint Server for Biology
C. L. McCaffertyE. M. Marcotte
December 3, 2020
Preprint
Open Access

A multi-task deep-learning system for predicting membrane associations and secondary structures of proteins

BioRxiv : the Preprint Server for Biology
BIAN LIJ. Meiler
December 17, 2020
Preprint
Open Access

Genotype-phenotype map of an RNA-ligand complex

BioRxiv : the Preprint Server for Biology
O. PuchtaGrzegorz Kudla
October 24, 2020
Open Access

Machine Learning Enables Selection of Epistatic Enzyme Mutants for Stability Against Unfolding and Detrimental Aggregation

Chembiochem : a European Journal of Chemical Biology
Guangyue LiManfred T Reetz
August 4, 2020

A New Framework for Automatic Detection of Patients With Mild Cognitive Impairment Using Resting-State EEG Signals

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
Siuly SiulyFrank Whittaker
October 31, 2020
Open Access

AlignmentViewer: Sequence Analysis of Large Protein Families

F1000Research
Roc ReguantNicholas Paul Gauthier
June 5, 2020

Predicting the stability of mutant proteins by computational approaches: an overview

Briefings in Bioinformatics
Anna MarabottiAngelo Facchiano
October 22, 2020
Open Access

Machine learning techniques for mortality prediction in critical traumatic patients: anatomic and physiologic variables from the RETRAUCI study

BMC Medical Research Methodology
Luis ServiáJavier Trujillano Cabello
December 20, 2020
Preprint
Open Access

Evolutionary coupling range varies widely among enzymes

BioRxiv : the Preprint Server for Biology
Julian Echave
July 21, 2020
Open Access

Machine learning through cryptographic glasses: combating adversarial attacks by key-based diversified aggregation

EURASIP Journal on Information Security
Olga TaranSlava Voloshynovskiy

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