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).

• Transcription network construction for large-scale microarray datasets using a high-performance computing approach.

  PMID 18366618 · PMC2386070 · BMC genomics · 2008 · 8 claims · 7 setups

  Full-text index only

  RMT removes the random noise component of the gene expression correlation matrix by testing its eigenvalue statistics against a null hypothesis derived from a truly random correlation matrix

  yeast liver eight-node microarray k-means hybrid

• Parsimonious Gene Correlation Network Analysis (PGCNA): a tool to define modular gene co-expression for refined molecular stratification in cancer.

  PMID 30993001 · PMC6459838 · NPJ systems biology and applications · 2019 · 8 claims · 7 setups

  Has reproduction · 71

  Retaining only the top ~3 most correlated edges per gene (EPG3) combined with FastUnfold clustering (termed PGCNA) produces gene co-expression modules with significantly better separation and enrichment of known biology than using all edges or other clustering methods.

  breast colorectal brca representative gene comparative multi-omic

• The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists.

  PMID 17784955 · PMC2375021 · Genome biology · 2007 · 8 claims · 6 setups

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  Gene-gene functional similarity can be measured using kappa statistics applied to a binary gene-annotation-term matrix built from 14 annotation categories.

  genome protein-protein genes artificial kappa clustering gene

• ScLRTC: imputation for single-cell RNA-seq data via low-rank tensor completion.

  PMID 34844559 · PMC8628418 · BMC genomics · 2021 · 8 claims · 8 setups

  Has reproduction · 85

  scLRTC imputes dropout entries closest to the original expression values on simulated datasets, outperforming other state-of-the-art methods by SSE and PCC.

  usoskin pollen zeisel yan scrna-seq umap masking