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).
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Has reproduction · 87
Forseti: a mechanistic and predictive model of the splicing status of scRNA-seq reads.
PMID 38940130 · PMC11256924 · Bioinformatics (Oxford, England) · 2024 · 7 claims · 5 setups
Forseti is the first probabilistic model for resolving the splicing status of exonic scRNA-seq reads by scoring putative fragments linking read alignments to proximate priming sites
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Has reproduction · 42
KAGE: fast alignment-free graph-based genotyping of SNPs and short indels.
PMID 36195962 · PMC9531401 · Genome biology · 2022 · 7 claims · 7 setups
KAGE combines population-based kmer count modeling with single-variant prior adjustment into an alignment-free genotyper that matches the accuracy of the best existing alignment-free genotypers while being an order of magnitude faster.
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Full-text index only
Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.
PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups
CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.
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Has reproduction · 88
Comprehensive benchmarking of large language models for RNA secondary structure prediction.
PMID 40205851 · PMC11982019 · Briefings in bioinformatics · 2025 · 7 claims · 4 setups
Existing RNA-LLMs had not previously been evaluated for secondary structure prediction in a unified, fair experimental setup with the same datasets and prediction model.
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Full-text index only
In silico segmentations of lentivirus envelope sequences.
PMID 17376229 · PMC1847453 · BMC bioinformatics · 2007 · 8 claims · 8 setups
C and V regions of lentivirus SU sequences have distinct statistical (oligonucleotide/amino-acid) compositions that HMMs can learn and use to delimit them.