AIMC Topic: Mutation
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Holistic understanding of trimethoprim resistance in using an integrative approach of genome-wide association study, resistance reconstruction, and machine learning.
mBio
Aug 9, 2024
UNLABELLED: Antimicrobial resistance (AMR) is a public health threat worldwide. Next-generation sequencing (NGS) has opened unprecedented opportunities to accelerate AMR mechanism discovery and diagnostics. Here, we present an integrative approach to...
Predicting telomerase reverse transcriptase promoter mutation in glioma: A systematic review and diagnostic meta-analysis on machine learning algorithms.
The neuroradiology journal
Aug 5, 2024
BackgroundGlioma is one of the most common primary brain tumors. The presence of the telomerase reverse transcriptase promoter (pTERT) mutation is associated with a better prognosis. This study aims to investigate the TERT mutation in patients with g...
Machine learning-guided multi-site combinatorial mutagenesis enhances the thermostability of pectin lyase.
International journal of biological macromolecules
Aug 5, 2024
Enhancing the thermostability of enzymes is crucial for industrial applications. Methods such as directed evolution are often limited by the huge sequence space and combinatorial explosion, making it difficult to obtain optimal mutants. In recent yea...
Integrating knowledge graphs into machine learning models for survival prediction and biomarker discovery in patients with non-small-cell lung cancer.
Journal of translational medicine
Aug 5, 2024
Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant challenge for the scientific and clinical community despite decades of advanced analytics. Addressing this challenge not only helps inform the critical...
Deep mutational scanning and machine learning for the analysis of antimicrobial-peptide features driving membrane selectivity.
Nature biomedical engineering
Jul 31, 2024
Many antimicrobial peptides directly disrupt bacterial membranes yet can also damage mammalian membranes. It is therefore central to their therapeutic use that rules governing the membrane selectivity of antimicrobial peptides be deciphered. However,...
A stemness-based signature with inspiring indications in discriminating the prognosis, immune response, and somatic mutation of endometrial cancer patients revealed by machine learning.
Aging
Jul 30, 2024
Endometrial cancer (EC) is a fatal gynecologic tumor. Bioinformatic tools are increasingly developed to screen out molecular targets related to EC. Our study aimed to identify stemness-related prognostic biomarkers for new therapeutic strategies in E...
Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome.
PLoS computational biology
Jul 30, 2024
Melanoma showcases a complex interplay of genetic alterations and intra- and inter-cellular morphological changes during metastatic transformation. While pivotal, the role of specific mutations in dictating these changes still needs to be fully eluci...
Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering.
Nature communications
Jul 29, 2024
The effective design of combinatorial libraries to balance fitness and diversity facilitates the engineering of useful enzyme functions, particularly those that are poorly characterized or unknown in biology. We introduce MODIFY, a machine learning (...
EnzyACT: A Novel Deep Learning Method to Predict the Impacts of Single and Multiple Mutations on Enzyme Activity.
Journal of chemical information and modeling
Jul 22, 2024
Enzyme engineering involves the customization of enzymes by introducing mutations to expand the application scope of natural enzymes. One limitation of that is the complex interaction between two key properties, activity and stability, where the enha...
DEL-Thyroid: deep ensemble learning framework for detection of thyroid cancer progression through genomic mutation.
BMC medical informatics and decision making
Jul 22, 2024
Genes, expressed as sequences of nucleotides, are susceptible to mutations, some of which can lead to cancer. Machine learning and deep learning methods have emerged as vital tools in identifying mutations associated with cancer. Thyroid cancer ranks...
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