Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Showing 9361-9380 of 14,220 articles

CanID: a robust and accurate RNAseq Expression-based diagnostic classification scheme for pediatric malignancies

Cancer subtype classification is critical for precision therapy and there is a growing trend of augmenting histopathology testing procedures with omics-based machine learning classifiers. However, analytical challenges remain for pediatric cancer on the scope and precision of the current classifiers as well as the evolving subtype standardization. To address these challenges, we built Cancer Ident...

Explainable machine learning-assisted exploration of chromatin dynamics reveals chromosome-specific response to serum starvation

Chromatin is dynamic at all length scales, influencing chromatin-based processes, such as gene expression. Even large-scale reorganization of whole chromosome territories has been reported upon specific signals, but lack of suitable methods has prevented analysis of the underlying dynamic processes. Here we have used CRISPR-Sirius for time-lapse imaging of chromatin loci dynamics during serum star...

Intra-DNA k-mer Conservation Patterns Encode Evolutionary Selection of Variants

Evolution shapes the structure and content of genomes, yet the contribution of local sequence composition to variant selection remains poorly understo...

CLM-access: A Specialized Foundation Model for High-dimensional Single-cell ATAC-seq analysis

Inspired by the success of large language models (LLMs) in natural language processing, cell language models (CLMs) have emerged as a promising paradi...

Predicting flowering time using integrated morphophysiological and genomic data with machine learning models

Indigenous Cannabis Sativa populations have adapted to diverse environments, resulting in genetic and phenotypic diversity. Understanding the mechanis...

Integrated histopathologic modeling of detailed tumor subtypes and actionable biomarkers

Accurate cancer subtyping with accompanying molecular characterization is critical for precision oncology. While machine learning approaches have been...

SkeletAge: Transcriptomics-based Aging Clock Identifies 26 New Targets in Skeletal Muscle Aging

Identifying the set of genes that regulate baseline healthy aging – aging that is not confounded by illness – is critical to understating aging biolog...

Calcium Binding Affinity in the Mutational Landscape of Troponin-C: Free Energy Calculation, Coevolution Modeling and Machine Learning

Mutation in calcium-binding proteins (CBPs) can significantly influence Ca2+ binding affinity (BA), resulting in substantial impairment in the signali...

Colorectal cancer heterogeneity co-evolves with tumor architecture to determine disease outcome

Intratumoral heterogeneity, originating from genetic, epigenetic, and phenotypic cellular diversity, is pervasive in cancer. As these heterogeneous st...

Multimodal learning decodes the global binding landscape of chromatin-associated proteins

Chromatin-associated proteins (CAPs), including over 1,600 transcription factors, bind directly or indirectly to the genomic DNA to regulate gene expr...

DeepPROTECTNeo: A Deep learning-based Personalized and RV-guided Optimization tool leveraging TCR Epitope interaction using Context-aware Transformers

The development of personalized cancer vaccines relies heavily on accurately identifying neoepitopes capable of eliciting strong immune responses. T c...

CpGPT: a Foundation Model for DNA Methylation

DNA methylation is a type of epigenetic modification that plays a significant role in development, aging, and disease. Despite extensive research into...

CART-GPT: A T Cell-Informed AI Linguistic Framework for Interpreting Neurotoxicity and Therapeutic Outcomes in CAR-T Therapy

Chimeric antigen receptor (CAR) T cell therapy holds transformative potential for hematologic malignancies, yet predicting patient-specific treatment ...

ProStab: Prediction of protein stability change upon mutations by protein language and inverse folding models

Predicting protein stability change upon mutation is critical for protein engineering, yet remains limited by the modeling assumptions of physics-base...

AVDB: The Arab Variation and Disease Burden Database

Public genomic databases are crucial to precision medicine but often lack representation from Arab populations, which have distinct genetic structures...

EpiPred: A gene-specific machine learning model for classifying missense variants in the epilepsy-related gene STXBP1

Missense variants in the STXBP1 gene are a frequent cause of early-onset developmental and epileptic encephalopathies and related neurodevelopmental d...

DynaRepo: The repository of macromolecular conformational dynamics

Proteins, RNA, and DNA are central to virtually all cellular processes, often assembling into macro-molecular complexes to perform their functions. Wh...

Identifying pyrogenic contaminants using transcriptomic profiling of monocyte activation test with machine learning

The monocyte activation test is an in vitro pyrogenicity assessment method that can utilise human peripheral blood mononuclear cells to detect pyrogen...

Limitations of de novo sequencing in resolving sequence ambiguity

De novo peptide sequencing enables peptide identification from fragmentation spectra without relying on sequence databases. However, incomplete spectr...

Understanding Language Model Scaling on Protein Fitness Prediction

Protein language models, and models that incorporate structure or homologous sequences, estimate sequence likelihoods p(sequence) that reflect the pro...

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