TrendBio

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BACKFILLED Code and industry signals are partial for backfilled days.

Rank 1

Genomics

Computational scoring of variant effects on dosage, stability, and binding

Recent work calibrates in-frame indel predictors for ACMG/AMP use and extends variant scoring to dosage, stability, and RNA-binding constraints.

2 preprints · 5 published · ↑ 3.3× vs 4-wk avg
Rank 2

Structural bio & protein design

MD and adaptive sampling resolve functional states in membrane and regulatory proteins

Recent work pairs MD with weighted ensemble, k-means clustering, and steered MD to resolve ion selectivity and interface specificity.

2 preprints · 3 published · ↑ 2.7× vs 4-wk avg
Rank 3

ML / AI methods

Sequence-based models predict microbial traits, phage host specificity, and drug uptake

Interpretable and leakage-controlled models now link sequence to phage depolymerase specificity, protein expression, and cefiderocol uptake variants.

4 preprints · 1 published · ↑ 2.7× vs 4-wk avg
Rank 4

Systems biology

Computational models nominate perturbations that rescue diseased metabolic states

Transcriptomic and screening data are now being converted into testable intervention predictions across viral, cardiac, and glioma systems.

3 preprints · 2 published · ↑ 2.7× vs 4-wk avg
Rank 5

Single-cell

Omics integration methods benchmarked across transcriptomic and proteomic modalities

Growing single-cell and multi-omic datasets require integration methods whose performance is now tested against defined benchmarks and reference data.

6 preprints · 5 published · ↑ 2.3× vs 4-wk avg
Rank 6 Spatially resolved ligand-receptor and cell-proximity inference from transcriptomic data↑ 2.5×Single-cellRank 7 Structure-based tools score protein interfaces, ligand binding modes and cryptic sites↑ 2.3×Structural bio & protein designRank 8 Deep networks predict drug interactions, molecular structures and RNA modification sites↑ 2.4×ML / AI methodsRank 9 Computational inference of microbial traits from genomic and transcriptomic data↑ 2.4×Systems biologyRank 10 ML and physics methods' generalization under out-of-distribution splits↑ 2.3×ML / AI methodsRank 11 Computational tools model B cell receptor evolution, chain pairing, and CAR responses↑ 2.1×Single-cellRank 12 Biologically constrained deep learning integrates spatial, chromatin, and imaging data↑ 2.1×ML / AI methodsRank 13 Machine-learning-guided de novo design of protein and peptide binders↑ 2.2×Structural bio & protein designRank 14 Nonlinear models yield emergent transitions in signaling, fate and tumor dynamics↑ 2.3×Systems biologyRank 15 Free-energy and frustration methods link protein states to selectivity and catalysis↑ 2.1×Structural bio & protein designRank 16 Reproducible workflows and benchmarks for sequencing analysis tools across assay types↑ 1.9×Tools & infrastructureRank 17 Verifiable FDR reporting and uncertainty-aware isoform quantification in proteomics↑ 2.0×ProteomicsRank 18 Graph, manifold and tensor methods resolve spatial and single-cell tissue structure↑ 1.8×TranscriptomicsRank 19 Computational models infer metabolic fluxes and kinetic parameters from omics dataMetabolomicsRank 20 Refined inference of tumor methylation, structural variants and clonal structureEpigenomics