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).

Publications 1.3k Datasets 392.5k Experiments 21

System / cell line: svm ✕ Assay: sensitivity ✕ Clear

Identification of diagnostic markers for tuberculosis by proteomic fingerprinting of serum.

PMID 16980117 · PMC7159276 · Lancet (London, England) · 2006 · 8 claims · 5 setups

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An SVM classifier trained on serum proteomic profiles discriminated patients with active tuberculosis from controls with clinically overlapping conditions

serum computational kda spin-column seldi-tof supervised peptide
Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine.

PMID 16381612 · PMC1360673 · BMC bioinformatics · 2005 · 7 claims · 7 setups

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A 32-dimensional triplet structure-sequence feature vector combined with SVM (triplet-SVM) can distinguish real human pre-miRNAs from pseudo pre-miRNA hairpins with ~90% accuracy.

pre-mirnas test conserved-hairpin cross-species secondary svm cross-species
Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach.

PMID 18834544 · PMC2575220 · BMC bioinformatics · 2008 · 8 claims · 8 setups

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128 discriminating 4-mer motifs combined with an SVM (RBF kernel, LIBSVM) can distinguish promoter from non-promoter DNA sequences

plant drosophila promoter same 4-mer tata blast
Exhaustive prediction of disease susceptibility to coding base changes in the human genome.

PMID 18793467 · PMC2537574 · BMC bioinformatics · 2008 · 8 claims · 7 setups

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Inter-species conservation is the strongest single predictor of disease-associated coding mutations among the factors tested.

hgmd refseq aligned svm svm reciprocal inter-species
Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines.

PMID 18005451 · PMC2216041 · BMC bioinformatics · 2007 · 8 claims · 5 setups

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Parepro, an SVM-based method integrating three attribute sets (RD, MI, IE) derived from evolutionary and residue-property information, predicts whether an nsSNP is deleterious or neutral.

sequences target svm benchmark homology
Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning.

PMID 34575658 · PMC8472680 · Journal of personalized medicine · 2021 · 6 claims · 4 setups

Has reproduction · 86

A training gene set of 719 unique upregulated DEGs (subtype-specific) can be used to build ML models that classify TNBC into BLIA, BLIS, MES, and LAR subtypes.

known tnbc unique unknown gene machine term
Prediction of candidate primary immunodeficiency disease genes using a support vector machine learning approach.

PMID 19801557 · PMC2780952 · DNA research : an international journal for rapid publication of reports on genes and genomes · 2009 · 6 claims · 3 setups

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An SVM trained on 69 binary features of known PID genes can accurately classify PID vs non-PID genes and predict novel candidate PID genes

genome training svm support leave-one-out sensitivity
Discovery and identification of potential biomarkers of papillary thyroid carcinoma.

PMID 19785722 · PMC2761863 · Molecular cancer · 2009 · 8 claims · 7 setups

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A 3-peak (m/z 9190, 6631, 8697 Da) SVM classification model discriminates PTC from non-cancer controls with high sensitivity and specificity

serum hplc-purified trypsin-digested crude seldi-tof-ms solid-phase maldi-tof-ms
Local combinational variables: an approach used in DNA-binding helix-turn-helix motif prediction with sequence information.

PMID 19651875 · PMC2761287 · Nucleic acids research · 2009 · 8 claims · 7 setups

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The LCV approach predicts HTH motifs with 93.29% accuracy, 93.93% sensitivity and 92.66% specificity using only primary sequence information

quintessentialset-88 hth same newly lcs svm traditional
MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features.

PMID 17553836 · PMC1933124 · Nucleic acids research · 2007 · 8 claims · 8 setups

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A hybrid feature combining local contiguous triplet structure-sequence composition, MFE of the secondary structure, and P-value of a randomization test improves classification of real vs pseudo pre-miRNAs

real combined pre-mirna training random independent repeated
A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection.

PMID 19828085 · PMC2762074 · BMC bioinformatics · 2009 · 7 claims · 1 setups

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A scale-space based unsupervised feature extraction method combined with SVM classification achieves high accuracy in ovarian cancer detection from serum mass spectra.

serum high-resolution
Application of Machine Learning in Predicting Hepatic Metastasis or Primary Site in Gastroenteropancreatic Neuroendocrine Tumors.

PMID 37887568 · PMC10605255 · Current oncology (Toronto, Ont.) · 2023 · 8 claims · 7 setups

Has reproduction · 59

Multi-gene random forest models classify primary tumor vs. liver metastasis samples with 100% accuracy in training/test cohorts and >90% accuracy in an independent validation cohort

pancreatic rna-seq liver tumor bulk machine multi-label
A comparison of classification methods for predicting Chronic Fatigue Syndrome based on genetic data.

PMID 19772600 · PMC2765429 · Journal of translational medicine · 2009 · 7 claims · 3 setups

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The naive Bayes model with the wrapper-based feature selection approach performed best among all predictive models tested for distinguishing CFS from controls.

subjects naive svm c4.5
Boosting accuracy of automated classification of fluorescence microscope images for location proteomics.

PMID 15207009 · PMC449699 · BMC bioinformatics · 2004 · 8 claims · 8 setups

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New classifiers (SVMs, ensembles) and new wavelet-derived (Gabor, Daubechies) features improve recognition of protein subcellular location patterns over the previous neural network approach

hela automated stepwise training-set-size
Zebrafish whole-adult-organism chemogenomics for large-scale predictive and discovery chemical biology.

PMID 18618001 · PMC2442223 · PLoS genetics · 2008 · 8 claims · 6 setups

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Zebrafish whole-adult-organism chemogenomics generates robust prediction models that discriminate P(H)AHs from ECs across independent experiments

zebrafish computational seven consolidated whole-adult-organism supervised quantitative
Predicting Bone Metastasis Using Gene Expression-Based Machine Learning Models.

PMID 34858485 · PMC8631472 · Frontiers in genetics · 2021 · 7 claims · 5 setups

Has reproduction · 62

A DNN model using the top 34 betweenness-centrality-ranked hub genes predicts bone metastasis with AUC of 92.11% on the GEO validation data.

breast degs geo tcga gene protein-protein machine
Logical Analysis of Data (LAD) model for the early diagnosis of acute ischemic stroke.

PMID 18616825 · PMC2492849 · BMC medical informatics and decision making · 2008 · 7 claims · 5 setups

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An LAD classification model built from a support-set of 3 peptide peaks can distinguish stroke patients from controls with 75% accuracy on an independent validation set

plasma discretized seldi-tof serum logical
Scalable Prediction of Acute Myeloid Leukemia Using High-Dimensional Machine Learning and Blood Transcriptomics.

PMID 31918046 · PMC6992905 · iScience · 2020 · 8 claims · 8 setups

Has reproduction · 96

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.

peripheral pbmc datasets hg-u133 gene bulk machine
Cataloging coding sequence variations in human genome databases.

PMID 18974781 · PMC2570488 · PloS one · 2008 · 8 claims · 7 setups

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A significant proportion of CVs overlap between HGMD and dbSNP (4.36% of HGMD CVs registered in dbSNP; 8.11% of dbSNP CVs registered in HGMD), warranting caution when interpreting phenotypic relevance of concurrent CVs.

coding hapmap concurrent nssnps database hapmap amino
Genomic variation in myeloma: design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival.

PMID 18778477 · PMC2553089 · BMC medicine · 2008 · 7 claims · 7 setups

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A custom BOAC SNP panel of 3404 SNPs in 983 genes was developed using the Affymetrix GeneChip Targeted Genotyping Platform, focused on non-synonymous coding SNPs and regulatory-region SNPs in candidate genes.

coriell myeloma duplicate snp targeted genotyping machine

Experiments

Identification of diagnostic markers for tuberculosis by proteomic fingerprinting of serum.

Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine.

Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach.

Exhaustive prediction of disease susceptibility to coding base changes in the human genome.

Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines.

Molecular Classification Models for Triple Negative Breast Cancer Subtype Using Machine Learning.

Prediction of candidate primary immunodeficiency disease genes using a support vector machine learning approach.

Discovery and identification of potential biomarkers of papillary thyroid carcinoma.

Local combinational variables: an approach used in DNA-binding helix-turn-helix motif prediction with sequence information.

MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features.

A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection.

Application of Machine Learning in Predicting Hepatic Metastasis or Primary Site in Gastroenteropancreatic Neuroendocrine Tumors.

A comparison of classification methods for predicting Chronic Fatigue Syndrome based on genetic data.

Boosting accuracy of automated classification of fluorescence microscope images for location proteomics.

Zebrafish whole-adult-organism chemogenomics for large-scale predictive and discovery chemical biology.

Predicting Bone Metastasis Using Gene Expression-Based Machine Learning Models.

Logical Analysis of Data (LAD) model for the early diagnosis of acute ischemic stroke.

Scalable Prediction of Acute Myeloid Leukemia Using High-Dimensional Machine Learning and Blood Transcriptomics.

Cataloging coding sequence variations in human genome databases.

Genomic variation in myeloma: design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival.