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BACKFILLED Code and industry signals are partial for backfilled days.

Rank 1

ML / AI methods

Neural fusion and graph models integrate omics and imaging for patient-level prediction

Recent November 2025 papers extend deep fusion, graph and kernel methods to missing-modality, spatial and single-cell multi-omics data.

21 published · ↑ 3.4× vs 4-wk avg
Rank 2

ML / AI methods

ML models span ligand kinetics, peptide design, and zero-shot ligand generation

Recent items pair generative and predictive models with benchmarking under distribution shift and generalization to unseen protein targets.

1 preprint · 9 published · ↑ 1.9× vs 4-wk avg
Rank 3

Genomics

Computational tools advance variant detection, effect prediction, and SV benchmarking

Recent preprints and publications report deep-learning and transformer models for long-read mosaic calling and variant effect prediction.

2 preprints · 6 published · ↑ 1.6× vs 4-wk avg
Rank 4

ML / AI methods

PLM embeddings with task-specific architectures predict diverse biological functions

Recent published frameworks pair pretrained protein language model embeddings with structural information and task-specific deep architectures.

9 published · ↑ 1.7× vs 4-wk avg
Rank 5

ML / AI methods

Deep sequence models predict RNA, DNA and protein modification and binding sites

Transfer-learning and attention architectures are now applied across plant methylation, ncRNA classification, and transcription factor binding prediction.

9 published · ↑ 1.7× vs 4-wk avg
Rank 6 Comparative benchmarks and tools for noisy sequencing data across platforms and taxa↑ 1.6×Single-cellRank 7 Computational predictors of protein binding affinity, partners, and mutational effectsStructural bio & protein designRank 8 Benchmarks and tools for variant, copy number, and methylation analysis from sequencing…GenomicsRank 9 Inferring gene regulatory networks and transcriptional kinetics from single-cell…Systems biologyRank 10 Interpretable multimodal ML for drug toxicity, permeability and repurposingML / AI methodsRank 11 Packaged computational tools for single-cell, spatial, breeding, and metabolic analysisTools & infrastructureRank 12 Validated software tools for plasmid, virome, phage, and pathogen genomic analysisTools & infrastructureRank 13 Deep learning for drug synergy and interaction prediction with multimodal fusionML / AI methodsRank 14 LLMs are benchmarked for scRNA-seq cell-type annotation and RNA-seq metadata curationSingle-cellRank 15 Benchmarking and consensus scoring for RNA and nucleic acid structure predictionStructural bio & protein designRank 16 Faster sequence algorithms for alignment, motif scoring, genome sizing and DNA storageTools & infrastructureRank 17 Inference adaptations for relatedness, method disagreement, and genetic specificityGenomicsRank 18 Transformer and deep learning models advance proteomics risk and peptide predictionProteomicsRank 19 Pretrained language models for mRNA, metagenomic gene, and protein sequence tasksML / AI methodsRank 20 Network-based software frameworks now integrate multi-omics traits and holo-omics datasetsTools & infrastructure
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Rank 21 Inferring microenvironment trajectories from multi-timepoint spatial transcriptomicsTranscriptomicsRank 22 Generative and search-based sequence design guided by learned binding and immunogenicity…ML / AI methodsRank 23 Graph-based models resolve spatial domains and regulatory networks from transcriptomic…TranscriptomicsRank 24 Graph-network MD maps allosteric routes in Tat-TAR RNA; ligand screening benchmarkedStructural bio & protein designRank 25 Automated extraction and integration tools for bioinformatics workflows and metadataTools & infrastructureRank 26 Learned models assign sequences and tomogram voxels to discrete biological sourcesGenomicsRank 27 Computational inference for missing proteins and coexisting PTM isoformsProteomics

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