large language model

BOTANIC-0: a series of foundation models for plant genomic data

BOTANIC-0 models are plant genomic foundation models pretrained on diverse plant genomes, achieving competitive performance in genomic tasks like variant effect prediction.

h5adify: neuro-symbolic metadata harmonizationenables scalable AnnData integration with locallarge language models

h5adify harmonizes metadata from single-cell datasets using neuro-symbolic methods and local LLMs, improving integration and reducing batch effects.

AI-Guided CRISPR Screen Accelerates Discovery of New Drug Targets

This study uses a CRISPR screen and AI to identify new drug targets for psoriasis, finding ALOX5 and OXTR as promising candidates with validated therapeutic effects.

SummArIzeR: Simplifying cross-database enrichment result clustering and annotation via large language models

SummArIzeR clusters and annotates cross-database enrichment results using large language models, providing fast and unbiased interpretation of biological data.

CellSwarm: LLM-Driven Cell Agents Recapitulate Tumor Microenvironment Dynamics and Sense Indirect Genetic Perturbations

CELLSWARM uses LLM-driven agents to simulate tumor microenvironment dynamics, outperforming rule-based models in cross-cancer generalization and sensing indirect genetic perturbations.

Literature-derived, context-aware gene regulatory networks improve biological predictions and mathematical modeling

The paper develops a framework to assign context-dependent weights to gene regulations from literature, improving biological predictions and mathematical modeling of disease-specific networks.

MicrowellMicrofluidicsMiner (M3): Leverage Large Language Model Agents for Knowledge Mining of Microwell Microfluidics

This paper introduces M3, an LLM-based framework for knowledge mining in microwell microfluidics, achieving 78% accuracy in parameter extraction, significantly better than standalone LLM models.

Predicting Disease-Specific Histone Modifications and Functional Effects of Non-coding Variants by Leveraging DNA Language Models

The paper develops a disease-specific histone modification prediction model using a large language model and MoE architecture, achieving high AUROC scores and identifying AD-associated variants.

A custom phenotypic profile for Fanconi anemia: Addressing gaps in existing disease annotations

The paper develops a comprehensive HPO profile for Fanconi anemia by integrating clinical guidelines and LLM-based ontology extraction, identifying significant gaps in existing annotations.

scChat: A Large Language Model-Powered Co-Pilot for Contextualized Single-Cell RNA Sequencing Analysis

scChat is a large language model co-pilot for scRNA-seq analysis that integrates contextual reasoning to improve hypothesis generation and experimental design.

A Systematic Benchmark for Peptide Property Prediction

This paper introduces PPB, a benchmark for peptide property prediction, showing that large pre-trained models outperform others and highlighting challenges in clustering short peptides.

Large Language Model Agent for Modular Task Execution in Drug Discovery

AgentD, a GPT-4o agent wired to retrieval, generative, ADMET and Boltz-2 tools, chains early drug-discovery steps for BCL-2 and raised molecules with QED > 0.6 from 34 to 55.

PlasRAG: comprehensive plasmid characterization and retrieval through sequence-text alignment

PlasRAG characterizes and retrieves plasmids using sequence-text alignment, showing that plasmids with broader host ranges and ARGs spread more extensively.

PlotGDP: an AI Agent for Bioinformatics Plotting

PlotGDP provides an AI-powered web server for generating publication-quality bioinformatics plots using natural language commands without requiring coding or environment setup.

ChromSkills enables interpretable and reproducible agentic chromatin data analysis

ChromSkills provides a framework for reproducible and interpretable chromatin data analysis using domain-specific tools guided by LLMs.

BOLE: A Knowledge-Enhanced Multi-Agent Framework for Intelligent Genomic Breeding

BOLE translates high-level genomic breeding intent into validated workflows using a knowledge base and large language model reasoning.

BioVix: An Integrated Large Language Model Framework for Data Visualization, Graph Interpretation, and Literature-Aware Scientific Validation

BioVix integrates LLMs for data visualization, graph interpretation, and literature-aware validation in biological research.

An AI-Native Biofoundry for Autonomous Enzyme Engineering: Integrating Active Learning with Automated Experimentation

This paper introduces an AI-native biofoundry that uses natural language and active learning to autonomously engineer enzymes, achieving high hit rates and improved sequencing performance.

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis

scELMo uses Large Language Models to analyze single-cell data for clustering, batch correction, and cell-type annotation without retraining, outperforming existing methods.

Microbial general model: Leveraging large language model for contextualized microbiome analysis

The paper introduces MGM, a foundation model for microbiome analysis, showing improved classification and detection of dynamic patterns across diverse contexts.

Clinical and Cross-Domain Validation of an LLM-Guided, Literature-Based Gene Prioritization Framework

The paper validates an LLM-guided gene prioritization framework for sepsis and tests its generalizability to obesity and infection using clinical and proteomic data.

Zero-shot ecological annotation of microbial genomes with myLLannotator accelerates scientific discovery

myLLannotator uses a large language model to annotate microbial genomes, enabling rapid discovery of gene patterns in endosymbiotic bacteria.

An Agentic AI Framework for Ingestion and Standardization of Single-Cell RNA-seq Data Analysis

CellAtria automates scRNA-seq data ingestion and analysis through an AI agent and chatbot interface, reducing manual effort and increasing accessibility.

textToKnowledgeGraph: Generation of Molecular Interaction Knowledge Graphs Using Large Language Models for Exploration in Cytoscape

The paper introduces textToKnowledgeGraph, a tool using large language models to extract molecular interactions into BEL format for analysis in Cytoscape.

Generative single-cell transcriptomics via large language models

This paper introduces PGL, a large language model that generates synthetic single-cell RNA-seq data from metadata, enabling virtual cohort construction and reference-on-demand analysis.

Overcoming Topology Bias and Cold-Start Limita-tions in Drug Repurposing: A Clinical-Outcome-Aligned LLM Framework

This paper introduces a framework that improves drug repurposing by aligning LLM reasoning with clinical outcomes, overcoming topology bias and cold-start limitations.

Artificial Intelligence-Guided Design of CAR-T Cells for Solid Tumors through CD-Antigen Prioritization, Safety-by-Design Architectures, and Constrained Large Language Model Reasoning

This paper presents an AI-guided framework for designing CAR-T cells for solid tumors by integrating antigen prioritization, safety-by-design architectures, and LLM-assisted reasoning.

Cross-Domain Transfer Learning from Peptides to Lipids Using a Multi-Property Fine-Tuned LLM

The paper uses a multi-property fine-tuned language model to predict lipid retention times from peptide data, improving accuracy in data-sparse scenarios.

AI-Driven Knowledge Synthesis for Food WebParameterisation

This paper introduces a framework using LLMs to automate species grouping and diet matrix generation for food web construction, achieving high consistency in species grouping and moderate accuracy in trophic interactions.

Robin: An Advanced Tool for Comparative Loop Caller Result Analysis Leveraging Large Language Models

Robin provides a platform to analyze and compare loop caller results using Large Language Models, offering visualization and metrics like recovery and overlap.