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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Performance assessment of promoter predictions on ENCODE regions in the EGASP experiment.
PMID 16925837 · PMC1810552 · Genome biology · 2006 · 6 claims · 3 setups
Promoter predictors that combine promoter prediction with gene prediction (N-SCAN, Fprom) achieve better performance than pure ab initio promoter predictors, mainly by reducing the promoter search space and false positives
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Has reproduction · 84
Pharokka: a fast scalable bacteriophage annotation tool.
PMID 36453861 · PMC9805569 · Bioinformatics (Oxford, England) · 2023 · 8 claims · 5 setups
Pharokka is a one-line, fast, scalable bacteriophage annotation tool producing standards-compliant outputs, installable via a two-line bioconda command
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Automatic annotation of eukaryotic genes, pseudogenes and promoters.
PMID 16925832 · PMC1810547 · Genome biology · 2006 · 8 claims · 6 setups
Fgenesh++ gene prediction pipeline identifies 91% of coding nucleotides with 90% specificity
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Has reproduction · 68
Bayesian transcriptome assembly.
PMID 25367074 · PMC4397945 · Genome biology · 2014 · 8 claims · 8 setups
Bayesembler, a probabilistic transcriptome assembler built on a Bayesian model of the RNA sequencing process with Gibbs sampling over expressed candidates, abundances and read assignments, is introduced.
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SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells.
PMID 20008100 · PMC2836562 · Nucleic acids research · 2010 · 8 claims · 6 setups
SeqBuster is a versatile web-based and stand-alone bioinformatic toolkit for processing and analyzing large-scale small RNA deep sequencing datasets.
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Genome sequences and great expectations.
PMID 11178275 · PMC150431 · Genome biology · 2001 · 8 claims · 3 setups
Function is known or can be predicted for an average of 62% of proteins across 31 analyzed genomes.
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Analysis of protein sequence and interaction data for candidate disease gene prediction.
PMID 17020920 · PMC1636487 · Nucleic acids research · 2006 · 8 claims · 7 setups
Combining CPS and CMP using known disease genes as input achieves sensitivity 0.52 and specificity 0.97, reducing candidate lists 13-fold
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Evolutionary trace annotation of protein function in the structural proteome.
PMID 20036248 · PMC2831211 · Journal of molecular biology · 2010 · 8 claims · 7 setups
ET-ranked residue clusters can be used to build 3D templates that predict GO function in enzymes and non-enzymes alike, without prior knowledge of functional mechanism.
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Has reproduction · 96
Scalable Prediction of Acute Myeloid Leukemia Using High-Dimensional Machine Learning and Blood Transcriptomics.
PMID 31918046 · PMC6992905 · iScience · 2020 · 8 claims · 8 setups
Data-driven, high-dimensional ML approaches that learn multivariate signatures directly from genome-wide transcriptomic data (no prior gene selection) yield accurate and robust AML classifiers.
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Has reproduction · 84
Foster thy young: enhanced prediction of orphan genes in assembled genomes.
PMID 34928390 · PMC9023268 · Nucleic acids research · 2022 · 7 claims · 8 setups
Each of the five gene-prediction pipelines under-predicts orphan genes, with detection as low as 11% under one prediction scenario.
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How many human genes can be defined as housekeeping with current expression data?
PMID 18416810 · PMC2396180 · BMC genomics · 2008 · 8 claims · 4 setups
Current EST and microarray transcriptome sampling is far from saturated, limiting gene detectability and understanding of tissue-specific expression
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GENCODE: producing a reference annotation for ENCODE.
PMID 16925838 · PMC1810553 · Genome biology · 2006 · 8 claims · 8 setups
GENCODE annotation combines initial manual annotation by HAVANA, experimental validation, and refinement based on results to identify protein-coding genes in ENCODE regions