Genetics

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

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SHAP zero Explains Biological Sequence Models with Near-zero Marginal Cost for Future Queries

The growing adoption of machine learning models for biological sequences has intensified the need ...

Simultaneously Infer Cell Pseudotime,Velocity Field and Gene Interaction from Multi-Branch scRNA-seq Data with scPN

Modeling cellular dynamics from single-cell RNA sequencing (scRNA-seq) data is critical for unders...

A Surrogate Model for Quay Crane Scheduling Problem

In ports, a variety of tasks are carried out, and scheduling these tasks is crucial due to its sig...

DNAHLM -- DNA sequence and Human Language mixed large language Model

There are already many DNA large language models, but most of them still follow traditional uses, ...

Privacy-hardened and hallucination-resistant synthetic data generation with logic-solvers

Machine-generated data is a valuable resource for training Artificial Intelligence algorithms, eva...

DNA Language Model and Interpretable Graph Neural Network Identify Genes and Pathways Involved in Rare Diseases

Identification of causal genes and pathways is a critical step for understanding the genetic under...

DEL-Ranking: Ranking-Correction Denoising Framework for Elucidating Molecular Affinities in DNA-Encoded Libraries

DNA-encoded library (DEL) screening has revolutionized the detection of protein-ligand interaction...

Digital Humanities in the TIME-US Project: Richness and Contribution of Interdisciplinary Methods for Labour History

In 2015, the Annales journal, traditionally open to interdisciplinary approaches in history, refer...

Estimating the Causal Effects of T Cell Receptors

A central question in human immunology is how a patient's repertoire of T cells impacts disease. H...

BSM: Small but Powerful Biological Sequence Model for Genes and Proteins

Modeling biological sequences such as DNA, RNA, and proteins is crucial for understanding complex ...

PANACEA: Towards Influence-driven Profiling of Drug Target Combinations in Cancer Signaling Networks

Data profiling has garnered increasing attention within the data science community, primarily focu...

SGUQ: Staged Graph Convolution Neural Network for Alzheimer's Disease Diagnosis using Multi-Omics Data

Alzheimer's disease (AD) is a chronic neurodegenerative disorder and the leading cause of dementia...

Lower-dimensional projections of cellular expression improves cell type classification from single-cell RNA sequencing

Single-cell RNA sequencing (scRNA-seq) enables the study of cellular diversity at single cell leve...

KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors

DNA-Encoded Libraries (DEL) are combinatorial small molecule libraries that offer an efficient way...

Artificial intelligence techniques in inherited retinal diseases: A review

Inherited retinal diseases (IRDs) are a diverse group of genetic disorders that lead to progressiv...

A mechanistically interpretable neural network for regulatory genomics

Deep neural networks excel in mapping genomic DNA sequences to associated readouts (e.g., protein-...

Beyond the Alphabet: Deep Signal Embedding for Enhanced DNA Clustering

The emerging field of DNA storage employs strands of DNA bases (A/T/C/G) as a storage medium for d...

Assumption-Lean Post-Integrated Inference with Negative Control Outcomes

Data integration methods aim to extract low-dimensional embeddings from high-dimensional outcomes ...

Comparative Analysis of Multi-Omics Integration Using Advanced Graph Neural Networks for Cancer Classification

Multi-omics data is increasingly being utilized to advance computational methods for cancer classi...

BadCM: Invisible Backdoor Attack Against Cross-Modal Learning

Despite remarkable successes in unimodal learning tasks, backdoor attacks against cross-modal lear...

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