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).

• Constructing support vector machine ensembles for cancer classification based on proteomic profiling.

  PMID 16689692 · PMC5173238 · Genomics, proteomics & bioinformatics · 2005 · 7 claims · 4 setups

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  CSVME, built by selecting a subset of base SVMs via SVM-RFE ranking and fusing them with a trained upper-layer SVM, achieves better classification performance than an ensemble of all base SVMs.

  serum computational seldi-tof svm-rfe-based 10-fold

• 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

• Accurate splice site prediction using support vector machines.

  PMID 18269701 · PMC2230508 · BMC bioinformatics · 2007 · 8 claims · 5 setups

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  Weighted degree (WD) kernel SVMs outperform Markov Chains, GeneSplicer and SpliceMachine for genome-wide splice site recognition

  nn269 dgsplicer caenorhabditis arabidopsis svm genome-wide

• 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

• 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

• An SVM-based system for predicting protein subnuclear localizations.

  PMID 16336650 · PMC1325059 · BMC bioinformatics · 2005 · 7 claims · 3 setups

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  New kernels defined on k-peptide vectors mapped by BLOSUM62-based high-scored pair matrices (D1, D2, D3) improve SVM discrimination of protein subnuclear localization compared to conventional k-peptide encodings.

  single-localization multi-localization same svm sequence

• Integrative bioinformatics and artificial intelligence analyses of transcriptomics data identified genes associated with major depressive disorders including NRG1.

  PMID 37583471 · PMC10423927 · Neurobiology of stress · 2023 · 7 claims · 5 setups

  Has reproduction · 66

  Differentially expressed genes in MDD patients are enriched in immune response, inflammatory response, neurodegeneration, and cerebellar atrophy pathways.

  blood transcriptomic postmortem saliva gsea machine differential

• Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics.

  PMID 18053132 · PMC2254445 · BMC bioinformatics · 2007 · 6 claims · 5 setups

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  The paired oligo-border kernel (POBK) combined with SVMs predicts peptide adsorption/elution in SAX-SPE and retention time in IP-RP-HPLC more accurately than existing methods.

  peptides peptide sax-spe ip-rp-hplc cross-run

• 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

• 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

• 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

• Integrative transcriptomics and single-cell transcriptomics analyses reveal potential biomarkers and mechanisms of action in papillary thyroid carcinoma.

  PMID 40520228 · PMC12162626 · Frontiers in genetics · 2025 · 8 claims · 8 setups

  Has reproduction · 49

  ENTPD1, SERPINA1, and TACSTD2 are potential transcriptomic biomarkers for PTC

  ptc degs key bulk kegg weighted

• 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

• Discovery and validation of molecular patterns and immune characteristics in the peripheral blood of ischemic stroke patients.

  PMID 38650649 · PMC11034498 · PeerJ · 2024 · 8 claims · 8 setups

  Has reproduction · 83

  188 differentially expressed genes (DEGs) between IS and control blood samples were identified and enriched in immune-related biological pathways

  blood degs peripheral hub microarray kegg cibersort

• Systems spatiotemporal dynamics of traumatic brain injury at single-cell resolution reveals humanin as a therapeutic target.

  PMID 35951114 · PMC9372016 · Cellular and molecular life sciences : CMLS · 2022 · 8 claims · 8 setups

  Has reproduction · 98

  Coordinated gene expression patterns across cell types are disrupted and re-organized by mTBI with distinct regional, cellular, and temporal (24-h vs 7-day) specificity.

  hippocampus frontal peripheral cell-type single-cell svm-based ligand-receptor

• Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility.

  PMID 26538066 · PMC4634735 · BMC medical genomics · 2015 · 8 claims · 5 setups

  Has reproduction · 83

  A multigene peripheral-blood gene-expression biomarker accurately classifies which women from high-risk families develop familial breast cancer.

  peripheral pbmcs blood normal gene-expression lymphocyte gene

• Identification of TYR, TYRP1, DCT and LARP7 as related biomarkers and immune infiltration characteristics of vitiligo via comprehensive strategies.

  PMID 34107850 · PMC8806433 · Bioengineered · 2021 · 6 claims · 6 setups

  Has reproduction · 55

  TYR, TYRP1, DCT and LARP7 are biomarkers associated with vitiligo

  vitiligo merged robust gse90880 gene robust kegg

• Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.

  PMID 37691920 · PMC10485775 · Frontiers in immunology · 2023 · 8 claims · 8 setups

  Has reproduction · 55

  352 DEGs (198 up-regulated, 154 down-regulated) were identified between RPL and control endometrial samples

  endometrial degs hub decidua microarray wgcna machine

• 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

• Wiggle-predicting functionally flexible regions from primary sequence.

  PMID 16839194 · PMC1500818 · PLoS computational biology · 2006 · 7 claims · 6 setups

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  A GNM-derived, correlation-weighted 'FF score' can objectively define functionally flexible regions (FFRs) that match experimentally confirmed flexible/functional regions (hinges, recognition loops, catalytic loops).

  hiv bovine calmodulin nonredundant gaussian gnm support