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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From single cells to whole organisms.
PMID 16420683 · PMC1414103 · Genome biology · 2005 · 8 claims · 8 setups
The genetic-interaction map in S. cerevisiae is roughly four times as complex as the protein-protein interaction map, and genetic interactions do not overlap with physical interactions but instead predict functional neighborhoods
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Has reproduction · 73
treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses.
PMID 34001188 · PMC8127214 · Genome biology · 2021 · 7 claims · 6 setups
treeclimbR proposes multiple candidate resolutions on a tree and selects the optimal one in a data-driven manner using three criteria (FDR-controlling range of t, number of rejected leaves, fewest internal nodes)
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Iterative class discovery and feature selection using Minimal Spanning Trees.
PMID 15355552 · PMC520744 · BMC bioinformatics · 2004 · 7 claims · 5 setups
Iterating between MST-based clustering and t-statistic feature selection removes noise genes step-wise while sharpening the sample clustering
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On the analysis of glycomics mass spectrometry data via the regularized area under the ROC curve.
PMID 18076765 · PMC2211327 · BMC bioinformatics · 2007 · 8 claims · 4 setups
The TGDR-AUC algorithm regularizes the empirical AUC by replacing the non-differentiable 0-1 loss with a smooth sigmoid surrogate function and applies constrained threshold gradient descent regularization
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Identification of gene interactions associated with disease from gene expression data using synergy networks.
PMID 18234101 · PMC2258206 · BMC systems biology · 2008 · 8 claims · 4 setups
Synergy of a gene pair with respect to disease, defined as I(G1,G2;C) - [I(G1;C)+I(G2;C)], identifies gene pairs that interact cooperatively with respect to a phenotype rather than independently.
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Magnetically assisted DNA assays: high selectivity using conjugated polymers for amplified fluorescent transduction.
PMID 15905472 · PMC1131937 · Nucleic acids research · 2005 · 8 claims · 8 setups
Introducing streptavidin-coated magnetic microparticles (MMPs) into a sandwich-type CP-based DNA sensor significantly improves selectivity against non-cognate DNA compared with previously reported CP-amplified sensors.
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Estimation of relevant variables on high-dimensional biological patterns using iterated weighted kernel functions.
PMID 18509521 · PMC2396875 · PloS one · 2008 · 7 claims · 6 setups
wKIERA combines a weighted-kernel discriminant (kernel perceptron) with an iterative stochastic probability estimation-of-distribution algorithm to estimate a relevance distribution over variables
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Immunohistochemical and proteomic evaluation of nuclear ubiquitous casein and cyclin-dependent kinases substrate in invasive ductal carcinoma of the breast.
PMID 20069058 · PMC2801467 · Journal of biomedicine & biotechnology · 2009 · 7 claims · 5 setups
NUCKS is highly overexpressed in invasive ductal carcinoma (IDC) of the breast compared to matched normal tissue.
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With the finished human genome in hand, what next?
PMID 12844356 · PMC193627 · Genome biology · 2003 · 8 claims · 8 setups
Gene Ontology (GO) provides a syntax/query framework for functional classification of genes, expanding beyond E. coli origins into anatomy, pathology, and phenotype data.
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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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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.