Field Sample Study Analytical method Statistical method Performance Ref Clinical proteomics Sera Gaucher patients and healthy controls SELDI-TOF PCA-DA with variable selection by rank products Sg 89%; Spg 90% [91] Sera Breast cancer patients and healthy controls MALDI-MS PCA-DA with variable selection by rank products Sg 82%; Spg 86% [92] Ecotoxicology Mussels Exposition to oil pollution SELDI-TOF CART - [53] Clinical proteomics Proximal fluid samples Identify biosignatures of 3 breast cancer types: HER2 positive, hormone receptor positive and HER2 negative, triple negative (HER2-, ER-, PR-). Protein fractionation before LC-MS/MS CART - [54] Sera Characterization of the response to Infliximab in Crohn's disease: 20 patients with or without clinical response to Infliximab SELDI-TOF-MS CART Sg, Spg and accuracy in cross-validation: 78.6%, 80.0%and 79.3% [35] Sera Hepatocellular carcinoma: 81 patients with hepatitis B-related carcinoma and 80 controls SELDI-TOF CART Sgand Spg89.6%. Model with two biomarkers and AFP: Sg91.7%; Spg92.7%. [39] Urine Predictive diagnosis of chronic allograft dysfunction: 29 samples withdrawn 3 months post-transplant SELDI-TOF CART Sg 93%; Spg65%. [36] Clinical proteomics Platelets, peripheral blood mononuclear cells, plasma, urine and saliva Investigation of how fasting for 36h, as compared to 12h, affects the proteome of healthy volunteers 2DE, MS and multiplex immunoassay Random forests - [6] Sera Biomarker for Malignant Pleural Mesothelioma: 117 pathological cases and 142 asbestos-exposed controls SOMAmer proteomic technology Random forests Sg: 97% (training) – 90% (blinded verification); Spg 92% (training), 95% (blinded verification). Second validation set: Sg/Spg 90%/89%; combined accuracy 92%. [106] Plasma Biomarkers for multiple systemic autoimmune diseases in disease-discordant monozygotic twins: 4 pairs of systemic lupus erythematosus, 4 pairs of juvenile idiopathic arthritis, 2 pairs of juvenile dermatomyositis RP-LC-MS Random forests - [57] Sera Identification of lymphnode metastases in NSCLC with circulating autoantibody biomarkers 2-D immunoblots of HCC827 lysates for tumor-associated autoantigens Random forests Sg94%, Spg97%, NER% 96% [107] Blood NSCLC Immunoproteomic method Random forests NER%: 97% [108] Sera Biomarkers for prostate cancer 2D-DIGE Random forests - [19] Clinical proteomics Cytosolic protein extracts from frozen thyroid samples Biomarkers for follicular and papillary thyroid tumors: 10 follicular adenomas, 9 follicular carcinomas, 10 papillary carcinomas, 10 controls 2DE PLS-DA - [18] Urine Peptidomics LC/MS PCA and PLS-DA - [98] Sera Biomarkers of ovarian cancer: 265 sera from women admitted with symptoms of a pelvic mass MALDI-MS PCA and PLS-DA Best models: 79% Spg, 56% Sg, 68% accuracy [95] Cell line extracts Biomarkers for colon cancer (HCT116 cell line) treated and not treated with a new histone deacetylase inhibitor 2D-PAGE PLS-DA NER%=100% [17] Sera Biomarkers of resistance to neoadjuvant chemotherapy in advanced breast cancers: profiling of N-glycosylated proteins in 15 advanced breast cancer patients Label-free LC-MS/MS PLS-DA - [56] Cerebrospinal fluid Markers of multiple sclerosis (MS) and other neurological diseases (OND) vs. controls (NHC) Mas spectral profiling PLS-DA NER%: MS vs OND: MS 89.5%, OND: 92.3%. MS vs NHC: 100%. OND vs NHC: OND 97.2%, NHC 98.4% [96] Plasma Biomarkers of Alzheimer's disease progression: 119 samples of patients with mild cognitive impairment (MCI) with different outcomes Untargeted, label-free shotgun proteomics OPLS-DA Best model: accuracy 79%. Some sex-specific biomarkers were identified. [58] Clinical proteomics Sera Biomarkers of cancer (lymphoma and ovarian): determination of N-glycans of human serum alpha-1-acid glycoprotein   MALDI-TOF MS LDA NER% 88%. Cross-validation: cancerous vs. controls Sg 96%, Spg 93%; lymphoma vs. controls + ovarian tumor 72% Sg 84% Spg [28] Sera Development of a novel index FI-PRO in the prediction of fibrosis in chronic hepatitis C: 62 patients for training and 73 for validation. Prediction of minor fibrosis (F0-F1), moderate fibrosis (F2-F3) and cirrhosis (F4). - LDA Best model based on four markers. Novel index A2M/hemopexin: diagnostic performance rate 0.80-0.92 for F2-F4 and F3-F4 in validation [104] Plant biology Pinot Noir skins Biomarkers of ripening: 3 moments of ripening 2DE PCA and LDA NER%=100% in calibration; 77.78% in cross-validation [16] Animal biology Sera Biomarkers of ovine paratuberculosis (Johne's disease): sheep with paratuberculosis, vaccinated-exposed sheep and unexposed animals SELDI TOF–MS CART and LDA Accuracy: sheep vs unexposed or exposed 75-100% [38] Clinical proteomics Simulated data and a proteomic dataset Development of Ranking-PCA 2-DE Ranking-PCA NER%=100% [65] Differet samples Three different proteomic datasets: 1) 8 2DE maps from adrenal nude mouse glands (4 controls and 4 affected by neuroblastoma); 2) 11 samples from nuclea of human colon cancer HCT116 cell line (6 controls and 5 treated by an HDAC inhibitor); 3) 10 samples from total lysates of human colon cancer HCT116 cell line (5 controls and 5 treated by an HDAC inhibitor) 2-DE Ranking-PCA NER%=100% [64] Food analysis Meat extracts Biomarkers of tenderization of bovine Longissimus dorsi: 4 Charolaise heifers and 4 Charolaise bull’s muscles sampled at slaughter after early (12 days) and long ageing (26 days) Cartesian and polar 2-DE Ranking-PCA NER%: 100% [90] Clinical proteomics Cell line extracts Biomarkers for neuroblastoma 2-DE SIMCA NER%: 100% [21] Cell line extracts Biomarkers of mantle cell lymphoma 2DE SIMCA NER%: 100% [22] Cell line extracts Development of an approach  for identifying relevant proteins from SIMCA DPs 2DE SIMCA NER%: 100% [23] Clinical proteomics Sera Development of a sequence-specific exopeptidase activity test. Application to metastatic thyroid cancer patients (48) and controls (48) MALDI-TOF MS SVM 94% Sg and 90% Spg [29] Plasma Biomarkers of air contaminant exposure: Fischer rats exposed for 4h to clean air or Ottawa urban particles HPLC with autofluorescence detectio SVM and GA - [113] Sera Diagnosis of gastric adenocarcinoma. Test/training set: 120 gastric adenocarcinoma and 120 controls. Validation: 95 gastric adenocarcinoma and 51 controls. 29-plex array platform Random forests and SVM Training/test set: accuracy >88%. Validation set: >85%. [114] Cerebrospinal fluid Biomarkers of multiple sclerosis-related disorders: 107 patients with MS-related disorders (including relapsing remitting MS [RRMS], primary progressive MS [PPMS], anti-aquaporin4 antibody seropositive-neuromyelitis optica spectrum disorder [SP-NMOSD], and seronegative-NMOSD [SN-NMOSD]), amyotrophic lateral sclerosis (ALS), other inflammatory neurological diseases (controls). Independent sample set of 84 patients with MS-related disorders or with other neurological diseases. MALDI-TOF MS PCA and SVM SP-NMOSD and SN-NMOSD distinguishable from RRMS with high cross-validation accuracy by SVM [30] Sera Biomarkers of NSCLC: 8 NSCLC samples and 8 controls Label-free quantitative 1D-LC/MS/MS Normalized, randomly paired t test and integrated bioinformatics, including hierarchical clustering analysis, PCA and SVM - [59] Plasma Biomarkers of tuberculosis and malaria SELDI-TOF and MS SCCA and SVM Improvementsin diagnostic prediction, up to 11% in tuberculosis and up to 5% in malaria [112] Urine Biomarkers associated with early renal injury: 50 healthy controls and intensive care unit patients 12 - 24h after coronary artery bypass graft surgery SELDI-TOF MS SVM coupled to PCA - [37] Plasma - 2-D-LC-MS Regression analysis, unsupervised hierarchical clustering, PCA,  genetic algorithm and SVM 88% Sg and 94% Spg [51] Clinical proteomics Sera Identification of discriminatory variables in MS by clustering of variables (CLoVA). Two experimental data sets: ovarian and prostate cancers. MALDI-TOF and SELDI-TOF Self-organization maps for clustering of variables; classification methods: PLS-DA and ECVA Higher Sg and Spg than conventional PLS-DA and ECVA [115] Plasma Identification of a liver cirrhosis signature for predicting hepatocellular carcinoma risk in Hepatitis B carriers 174-antibody microarray system PCA, DLDA and 3-NN Accuracy, Sg and Spg: 100%, 100% and 90.9% respectively [119] Plasma Biomarkers for depression and schizophrenia: 245 depressed patients, 229 schizophrenic patients and 254 controls Multi analyte profiling evaluating  79 proteins PCA, PLS-DA and random forests - [99] Urine Biomarkers of pediatric nephrotic syndrome (NS): steroid-sensitive NS (SSNS), steroid-resistant NS (SRNS), and orthostatic proteinuria (OP). 19 subjects with SSNS/SDNS in remission, 14 with SSNS/SDNS in relapse, 5 with SRNS in relapse, and 6 with OP. SELDI-TOF MS Genetic algorithm and PCA - [40] Sera Evaluation of intact alpha-1-acid glycoprotein isoforms as potential biomarkers in bladder cancer: 16 samples (8 healthy, 8 bladder cancer) CZE-UV and CZE-ESI-MS ANOVA, PCA, LDA and PLS-DA. Best results obtained by LDA: NER%=93.75% [127] Tear fluid Biomarkers of breast cancer: 50 women with breast cancer and 50 age-matched controls SELDI-TOF MS multivariate discriminant analysis and ANN NER%: 71.19% for cancers, 70.69% for controls (overall NER=70.94%) [42] Urine Two studies: 1) addition of seven peptides at nanomolar concentrations to blank urine samples of different origin; 2) a study of urine from kidney patients with and without proteinuria. LC-MS PCA and NSC - [46] Plant biology Leaves of Arabidopsis thaliana Analysis oftime-related regulatory effects of plant metabolism at a systems level: wild type plants and starchless mutant plants deficient in phosphoglucomutase activity GC-TOF-MS- metabolite profiling and LC-MS- protein profiling PCA and ICA - [47] Clinical proteomics Sera and plasma Biomarkers of inflammatory auto-immune disease: 30 patients MALDI-TOF ICA - [24] Maternal plasma and cord plasma Biomarkers of spontaneous preterm birth: 191 African, American and Caucasian women - MARS - [121] - Improvement of mass spectra classification MALDI-TOF or SELDI-TOF MCR - [27] Plasma and bone-marrow cell extracts Biomarkers of acute myeloid or acute lymphoblastic leukemia: patients with Kawasaki disease and bone-marrow cell extracts from patients with acute myeloid or acute lymphoblastic leukemia SELDI-TOF-MS Preprocessing algorithm that clusters highly correlated features, using the Bayes information criterion to select an optimal number of clusters - [116] Proteomic datasets of ovarian and prostate cancer Development of a new approach to biomarker selection based on the application of several competing feature ranking procedures to compute a consensus list of features SELDI-TOF random forest, SVM, CART, LDA - [117] Sera Development of Nonnegative PCA. Four serum proteomic datasets: ovarian, ovarian-qaqc (quality assurance/quality control), liver and colorectal MS profiling nonnegative PCA and SVM   [81] Sera Biomarkers of Type 1 diabetes (T1D) SELDI-TOF Normal kernel discriminant analysis Training set: 88.9% Spg, 90.0% Sg. Test set: 82.8% Spg, 76.2% Sg [41]

Table 3: Applications of supervised methods in proteomics.