Papers

PDB-wide collection of binding data: current status of the PDBbind database.

A global reference for human genetic variation.

The Image Data Resource: A Bioimage Data Integration and Publication Platform.

A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.

The Human Cell Atlas.

Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12.

The Encyclopedia of DNA elements (ENCODE): data portal update.

Deep generative modeling for single-cell transcriptomics.

Predicting Splicing from Primary Sequence with Deep Learning.

scGen predicts single-cell perturbation responses.

Evaluating Protein Transfer Learning with TAPE.

The mutational constraint spectrum quantified from variation in 141,456 humans.

Cellpose: a generalist algorithm for cellular segmentation.

Highly accurate protein structure prediction with AlphaFold.

FLIP: Benchmark tasks in fitness landscape inference for proteins

AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.

The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans.

Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq.

ProtGPT2 is a deep unsupervised language model for protein design.

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning.

Robust deep learning-based protein sequence design using ProteinMPNN.

Evolutionary-scale prediction of atomic-level protein structure with a language model.

JUMP Cell Painting dataset: morphological impact of 136,000 chemical and genetic perturbations

Genomic benchmarks: a collection of datasets for genomic sequence classification.

Predicting cellular responses to complex perturbations in high-throughput screens.

Transfer learning enables predictions in network biology.

De novo design of protein structure and function with RFdiffusion.

Predicting transcriptional outcomes of novel multigene perturbations with GEARS.

Universal Cell Embeddings: A Foundation Model for Cell Biology

PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences.

AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences.

scGPT: toward building a foundation model for single-cell multi-omics using generative AI.

Large-scale foundation model on single-cell transcriptomics.

Chai-1: Decoding the molecular interactions of life

Protein language models learn evolutionary statistics of interacting sequence motifs.

Sequence modeling and design from molecular to genome scale with Evo.

Boltz-1 Democratizing Biomolecular Interaction Modeling

A cell atlas foundation model for scalable search of similar human cells.

Nucleotide Transformer: building and evaluating robust foundation models for human genomics.

CZ CELLxGENE Discover: a single-cell data platform for scalable exploration, analysis and modeling of aggregated data.

Simulating 500 million years of evolution with a language model.

Genome modeling and design across all domains of life with Evo 2

Scupa: single-cell unified polarization assessment of immune cells using the single-cell foundation model.

Scaling Large Language Models for Next-Generation Single-Cell Analysis

Virtual Cell Challenge: Toward a Turing test for the virtual cell.

Boltz-2: Towards Accurate and Efficient Binding Affinity Prediction

Predicting cellular responses to perturbation across diverse contexts with State

RiNALMo: general-purpose RNA language models can generalize well on structure prediction tasks.

rbio1 - training scientific reasoning LLMs with biological world models as soft verifiers

imAgeScore, a Cell Painting-Based Predictor of Cellular Age for High-throughput Drug Screening Applications

Machine learning for RNA secondary structure prediction: a review of current methods and challenges.

Illuminating cell states by a comprehensive and interpretable single cell foundation model.

Progress and new challenges in image-based profiling.

Crosstalk between RNA secondary and three-dimensional structure prediction: a comprehensive study.

Pre-training genomic language model with variants for better modeling functional genomics.

Automated Morphological Profiling via Deep Learning-Based Segmentation for High-Throughput Phenotypic Screening.

ITCNET: a visual and language pretraining model based on multimodal fusion in predicting the breast cancer subtypes on DCE-MRI.

Evolving computational paradigms for noncoding variant pathogenicity prediction.

Artificial Intelligence in genomics: a comprehensive survey of methods, resources, challenges, and prospects.

Comprehensive review and assessment of multi-species splicing variant prediction: task-specific deep learning models and genomic foundation models.

Inferring the qualities of protein-RNA models with graph transformers.

Machine Learning-Driven QSAR Modeling for pK<sub>a</sub> Prediction of Ionizable Lipids in Lipid Nanoparticles for Hepatic Gene Silencing.

How artificial intelligence is reshaping citation impact in oral and maxillofacial radiology journals: an 8-year analysis with editorial and clinical implications (JCR 2017-2024).

Machine Learning in Non-fullerene Organic Solar Cells: Accelerating Discovery, Design, and Understanding.

In vitro profiling of Trypanosoma cruzi inhibitors identified from High throughput Screening and application to parasite painting.

Accuracy of Deep Learning Models in Detecting Mandibular Furcation Defects on Panoramic Radiographs.

Application of Machine Learning in Predicting the Properties of Two-Dimensional Semiconductor Materials.

Machine Learning-Based Prediction of Polymer Properties Using Structure-Property Relationship Modeling.

Causal effect estimation from trans-regulatory single-cell CRISPR screens.

Protein Design Enters the Artificial Intelligence Era: Foundations, Tools, and Emerging Paradigms.

FourierDrug: a domain generalization framework for robust drug response prediction via frequency-space asymmetric attention.

Artificial intelligence applications in automated dental report generation - a scoping review.

Research progress of artificial intelligence in high-throughput drug screening.

Comparison of local large language models for extraction of signs and symptoms data from electronic health records.

Evaluation of Five Large Language Models for Parental Education in Pediatric Anesthesia: Reliability and Readability Study.

Artificial Intelligence in Selected Domains of Drug Discovery: A Critical Narrative Review.

A multi-modal co-attention model for accurate drug-target interaction prediction.

GARN3: A coarse-grained helix centered technique for RNA 3D structures prediction.

Trends in the use of adult-specific preference-weighted health-related quality of life instruments in clinical trials over the past 50 years: a protocol for a meta-research study using deep learning-based natural language processing and large language models.

Artificial intelligence in the diagnosis of deep vein thrombosis: A scoping review.