Genetics

Explainable convolutional neural network model provides an alternative genome-wide association perspective on mutations in SARS-CoV-2

Identifying mutations of SARS-CoV-2 strains associated with their phenotypic changes is critical for pandemic prediction and prevention. We compared an explainable convolutional neural network (CNN) approach and the traditional genome-wide association study (GWAS) on the mutations associated with WHO labels of SARS-CoV-2, a proxy for virulence phenotypes. We trained a CNN classification model th...

Knowledge-Guided Prompt Learning for Request Quality Assurance in Public Code Review

Public Code Review (PCR) is developed in the Software Question Answering (SQA) community, assisting developers in exploring high-quality and efficient review services. Current methods on PCR mainly focus on the reviewer's perspective, including finding a capable reviewer, predicting comment quality, and recommending/generating review comments. However, it is not well studied that how to satisfy ...

Diagnostic Performance of Deep Learning for Predicting Gliomas' IDH and 1p/19q Status in MRI: A Systematic Review and Meta-Analysis

Gliomas, the most common primary brain tumors, show high heterogeneity in histological and molecular characteristics. Accurate molecular profiling, ...

Absorb & Escape: Overcoming Single Model Limitations in Generating Genomic Sequences

Abstract Recent advances in immunology and synthetic biology have accelerated the development of deep generative methods for DNA sequence design. Tw...

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 for interpretable predictions, with Shapley values...

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 understanding cell development and underlying gene regul...

Uncovering the Genetic Basis of Glioblastoma Heterogeneity through Multimodal Analysis of Whole Slide Images and RNA Sequencing Data

Glioblastoma is a highly aggressive form of brain cancer characterized by rapid progression and poor prognosis. Despite advances in treatment, the u...

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 significant impact on productivity, making the genera...

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, such as extracting sequence features for classific...

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

Machine-generated data is a valuable resource for training Artificial Intelligence algorithms, evaluating rare workflows, and sharing data under str...

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 underpinnings of rare diseases. We propose novel approa...

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 interactions through read counts, enabling rapid exploration ...

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, referred to 'the current historiographical moment [as] ...

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. Here, we introduce a method to infer the causal eff...

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 processes like gene regulation and protein synthes...

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 focusing on structured data. In this paper, we introdu...

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, significantly impacting cost, mortality, and bur...

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 level. It provides a global view of cell-type specific...

Transcriptome and Redox Proteome Reveal Temporal Scales of Carbon Metabolism Regulation in Model Cyanobacteria Under Light Disturbance

We develop a systems approach based on an energy-landscape concept to differentiate interactions involving redox activities and conformational chang...

KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors

DNA-Encoded Libraries (DEL) are combinatorial small molecule libraries that offer an efficient way to characterize diverse chemical spaces. Selectio...