Experiments

Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).

• Application of alternative de novo motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites.

  PMID 34547062 · PMC8408018 · Vavilovskii zhurnal genetiki i selektsii · 2021 · 8 claims · 4 setups

  Has reproduction · 62

  MultiDeNA pipeline combines PWM, diPWM, BaMM and InMoDe models to train, evaluate, threshold, and classify ChIP-seq peaks for TFBS structural heterogeneity

  foxa2 genomic frequency chip-seq novo threshold

• maxATAC: Genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks.

  PMID 36719906 · PMC9917285 · PLoS computational biology · 2023 · 8 claims · 6 setups

  Has reproduction · 98

  maxATAC is a suite of deep neural network models enabling state-of-the-art, genome-scale TFBS prediction from ATAC-seq, with models for 127 human transcription factors

  lines hepg2 types single chip-seq omni-atac-seq atac-seq

• Predicting enhancers in mammalian genomes using supervised hidden Markov models.

  PMID 30917778 · PMC6437899 · BMC bioinformatics · 2019 · 8 claims · 8 setups

  Has reproduction · 70

  eHMM predicts enhancers with high precision and recall comparable to state-of-the-art methods and consistently outperforms them in accuracy and resolution

  esc atac-seq chip-seq cage

• Genomic prediction based on selective linkage disequilibrium pruning of low-coverage whole-genome sequence variants in a pure Duroc population.

  PMID 37853325 · PMC10583454 · Genetics, selection, evolution : GSE · 2023 · 5 claims · 6 setups

  Has reproduction

  SLDP selects a subset of WGS variants using GWAS prior information (P-value threshold) combined with LD pruning (r2) to improve genomic prediction accuracy.

  duroc discovery training real low-coverage genome-wide genomic