AIMC Topic: Evolution, Molecular

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Machine Learning of Protein Interactions in Fungal Secretory Pathways.

PloS one
In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict prote...

A new approach to the automatic identification of organism evolution using neural networks.

Bio Systems
Automatic identification of organism evolution still remains a challenging task, which is especially exiting, when the evolution of human is considered. The main aim of this work is to present a new idea to allow organism evolution analysis using neu...

Protein folds recognized by an intelligent predictor based-on evolutionary and structural information.

Journal of computational chemistry
Protein fold recognition is an important and essential step in determining tertiary structure of a protein in biological science. In this study, a model termed NiRecor is developed for recognizing protein folds based on artificial neural networks inc...

Systematic Analysis and Prediction of In Situ Cross Talk of O-GlcNAcylation and Phosphorylation.

BioMed research international
Reversible posttranslational modification (PTM) plays a very important role in biological process by changing properties of proteins. As many proteins are multiply modified by PTMs, cross talk of PTMs is becoming an intriguing topic and draws much at...

Protein contact prediction by integrating joint evolutionary coupling analysis and supervised learning.

Bioinformatics (Oxford, England)
MOTIVATION: Protein contact prediction is important for protein structure and functional study. Both evolutionary coupling (EC) analysis and supervised machine learning methods have been developed, making use of different information sources. However...

Better prediction of functional effects for sequence variants.

BMC genomics
Elucidating the effects of naturally occurring genetic variation is one of the major challenges for personalized health and personalized medicine. Here, we introduce SNAP2, a novel neural network based classifier that improves over the state-of-the-a...

Toll-like receptor signaling in vertebrates: testing the integration of protein, complex, and pathway data in the protein ontology framework.

PloS one
The Protein Ontology (PRO) provides terms for and supports annotation of species-specific protein complexes in an ontology framework that relates them both to their components and to species-independent families of complexes. Comprehensive curation o...

Bridging scales in cancer progression: mapping genotype to phenotype using neural networks.

Seminars in cancer biology
In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its pheno...

Comprehensive Characterization of Somatic Mutation Timing Reveals the Evolutionary Trajectory of Lung Adenocarcinoma in Chinese Patients.

Cancer research
UNLABELLED: Lung adenocarcinoma (LUAD) is a heterogeneous disease with substantial genomic differences between individuals of Chinese and European ancestries. Deciphering the timing of driver mutations may lead to insights into tumor evolution that c...

SARS-CoV-2: lessons in virus mutation prediction and pandemic preparedness.

Current opinion in immunology
The COVID-19 pandemic has prompted an unprecedented global response. In particular, extraordinary efforts have been dedicated toward monitoring and predicting variant emergence due to its huge impact, particularly for vaccine escape. Broadly, we clas...