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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Randomised trial of a decision aid and its timing for women being tested for a BRCA1/2 mutation.
PMID 14735173 · PMC2410151 · British journal of cancer · 2004 · 6 claims · 3 setups
The DA had no impact on well-being (anxiety, depression, cancer-related distress, general health)
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A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer.
PMID 17222328 · PMC1784097 · BMC cancer · 2007 · 7 claims · 8 setups
A workflow combining Alohomora, Mega2, MENDEL, SNPLINK and SimWalk2 enables linkage analysis with high-density SNP arrays in large pedigrees (>35-40 bits) that exceed the capacity of single existing programs
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Putting science over supposition in the arena of personalized genomics.
PMID 18665132 · PMC2531214 · Nature genetics · 2008 · 6 claims · 3 setups
There is a rapidly widening gap between gene-disease association discovery and research into the public health/clinical utility of that information.
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Introduction: the challenge of incidental findings.
PMID 18547190 · PMC2587006 · The Journal of law, medicine & ethics : a journal of the American Society of Law, Medicine & Ethics · 2008 · 8 claims · 5 setups
No consensus exists on how to handle incidental findings in human subjects research
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Review of state Comprehensive Cancer Control plans for genomics content.
PMID 15888219 · PMC1327702 · Preventing chronic disease · 2005 · 8 claims · 2 setups
18 of 30 state CCC plans analyzed contained genomics-related components, with wide variability in content
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CanPredict: a computational tool for predicting cancer-associated missense mutations.
PMID 17537827 · PMC1933186 · Nucleic acids research · 2007 · 8 claims · 7 setups
CanPredict is a web application providing public access to a random forest classifier that combines SIFT, LogR.E-value, and GOSS scores to predict whether a missense mutation is cancer-associated