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Mutation

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Detection of Breast Cancer Lump and BRCA1/2 Genetic Mutation under Deep Learning.

Computational intelligence and neuroscience
To diagnose and cure breast cancer early, thus reducing the mortality of patients with breast cancer, a method was provided to judge threshold of image segmentation by wavelet transform (WT). It was used to obtain information about the general area o...

-Complex-Based Machine Learning (HCML) for the Prediction of Protein-Protein Binding Affinity Changes upon Mutation.

Journal of chemical information and modeling
Protein-protein interactions (PPIs) are involved in almost all biological processes in the cell. Understanding protein-protein interactions holds the key for the understanding of biological functions, diseases and the development of therapeutics. Rec...

Experimental exploration of a ribozyme neutral network using evolutionary algorithm and deep learning.

Nature communications
A neutral network connects all genotypes with equivalent phenotypes in a fitness landscape and plays an important role in the mutational robustness and evolvability of biomolecules. In contrast to earlier theoretical works, evidence of large neutral ...

A new deep learning technique reveals the exclusive functional contributions of individual cancer mutations.

The Journal of biological chemistry
Cancers are caused by genomic alterations that may be inherited, induced by environmental carcinogens, or caused due to random replication errors. Postinduction of carcinogenicity, mutations further propagate and drastically alter the cancer genomes....

Boosted Sine Cosine Algorithm with Application to Medical Diagnosis.

Computational and mathematical methods in medicine
The sine cosine algorithm (SCA) was proposed for solving optimization tasks, of which the way to obtain the optimal solution is mainly through the continuous iteration of the sine and cosine update formulas. However, SCA also faces low population div...

Interpretable modeling of genotype-phenotype landscapes with state-of-the-art predictive power.

Proceedings of the National Academy of Sciences of the United States of America
Large-scale measurements linking genetic background to biological function have driven a need for models that can incorporate these data for reliable predictions and insight into the underlying biophysical system. Recent modeling efforts, however, pr...

Can machines learn the mutation signatures of SARS-CoV-2 and enable viral-genotype guided predictive prognosis?

Journal of molecular biology
MOTIVATION: Continuous emergence of new variants through appearance/accumulation/disappearance of mutations is a hallmark of many viral diseases. SARS-CoV-2 variants have particularly exerted tremendous pressure on global healthcare system owing to t...

Predicting CRISPR/Cas9 Repair Outcomes by Attention-Based Deep Learning Framework.

Cells
As a simple and programmable nuclease-based genome editing tool, the CRISPR/Cas9 system has been widely used in target-gene repair and gene-expression regulation. The DNA mutation generated by CRISPR/Cas9-mediated double-strand breaks determines its ...

An Animation Model Generation Method Based on Gaussian Mutation Genetic Algorithm to Optimize Neural Network.

Computational intelligence and neuroscience
With the rapid development of computer graphics, 3D animation has been applied to all fields of people's lives, especially in the industries of film and television works, games, and entertainment. The wide application of animation technology makes it...

DiaDeL: An Accurate Deep Learning-Based Model With Mutational Signatures for Predicting Metastasis Stage and Cancer Types.

IEEE/ACM transactions on computational biology and bioinformatics
Mutational signatures help identify cancer-associated genes that are being involved in tumorigenesis pathways. Hence, these pathways guide precision medicine approaches to find appropriate drugs and treatments. The pattern of mutations varies in diff...