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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scGeno: a Hidden Markov Model approach to denoise chromosome-scale genotypes from single-cell data.
PMID 41982479 · PMC13075984 · Bioinformatics advances · 2026 · 7 claims · 4 setups
scGeno, a categorical HMM, infers chromosome-level genotype states in mixed-genotype organisms by modeling sequential single-cell allelic expression ratios along chromosomes
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Has reproduction · 53
spliceJAC: transition genes and state-specific gene regulation from single-cell transcriptome data.
PMID 36321549 · PMC9627675 · Molecular systems biology · 2022 · 8 claims · 8 setups
spliceJAC uses unspliced and spliced mRNA count matrices to construct cell state-specific gene-gene regulatory interaction (Jacobian) matrices from scRNA-seq data
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Translating genome sequences into biological understanding.
PMID 12801409 · PMC193614 · Genome biology · 2003 · 8 claims · 7 setups
Gene-trap insertional mutagenesis in mouse ES cells (BayGenomics) generates a large resource of cell lines and knockout mice for studying gene expression patterns and function.
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Non-linear mapping for exploratory data analysis in functional genomics.
PMID 15661072 · PMC548129 · BMC bioinformatics · 2005 · 8 claims · 8 setups
A relaxation method for non-linear mapping adapts one pair of points per step rather than all points at once, and was originally shown by Chang and Lee to outperform Sammon's mapping in cluster detection effectiveness and computational efficiency.
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Exploration of the omics evidence landscape: adding qualitative labels to predicted protein-protein interactions.
PMID 17880677 · PMC2375035 · Genome biology · 2007 · 7 claims · 8 setups
Combining pairs of omics evidence types into two-dimensional 'evidence landscapes' allows regions to be identified that specifically and purely predict either physical or metabolic protein interactions