Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

[1]  Jiangshan J. Shen,et al.  Identification of 38 novel loci for systemic lupus erythematosus and genetic heterogeneity between ancestral groups , 2021, Nature Communications.

[2]  Liangjing Lu,et al.  Corrigendum to "Melatonin prevents endothelial dysfunction in SLE by activating the nuclear receptor retinoic acid-related orphan receptor-α" [Int. Immunopharmacol. 83 (2020) 106365]. , 2020, International immunopharmacology.

[3]  Ling Gao,et al.  The RBP1–CKAP4 axis activates oncogenic autophagy and promotes cancer progression in oral squamous cell carcinoma , 2020, Cell Death & Disease.

[4]  Christina B. Azodi,et al.  Opening the Black Box: Interpretable Machine Learning for Geneticists. , 2020, Trends in genetics : TIG.

[5]  K. Cain,et al.  Neutrophil and lymphocyte counts are associated with different immunopathological mechanisms in systemic lupus erythematosus , 2020, Lupus science & medicine.

[6]  A. Tommasini,et al.  Higher interferon score and normal complement levels may identify a distinct clinical subset in children with systemic lupus erythematosus , 2020, Arthritis Research & Therapy.

[7]  Liangjing Lu,et al.  Melatonin prevents endothelial dysfunction in SLE by activating the nuclear receptor retinoic acid-related orphan receptor-α. , 2020, International immunopharmacology.

[8]  Qing Zhou,et al.  New Horizons in the Genetic Etiology of Systemic Lupus Erythematosus and Lupus-Like Disease: Monogenic Lupus and Beyond , 2020, Journal of clinical medicine.

[9]  E. Kılıç,et al.  Evidence that melatonin downregulates Nedd4-1 E3 ligase and its role in cellular survival. , 2019, Toxicology and applied pharmacology.

[10]  F. Bonomini,et al.  NLRP3 Inflammasome Modulation by Melatonin Supplementation in Chronic Pristane-Induced Lupus Nephritis , 2019, International journal of molecular sciences.

[11]  Jan Komorowski,et al.  R.ROSETTA: an interpretable machine learning framework , 2019, BMC Bioinformatics.

[12]  I. Nabi,et al.  Reticulon and CLIMP-63 regulate nanodomain organization of peripheral ER tubules , 2019, bioRxiv.

[13]  Bilal Mirza,et al.  Machine Learning and Integrative Analysis of Biomedical Big Data , 2019, Genes.

[14]  M. Petri,et al.  Stratification of Systemic Lupus Erythematosus Patients Into Three Groups of Disease Activity Progression According to Longitudinal Gene Expression , 2018, Arthritis & rheumatology.

[15]  Andrzej Skowron,et al.  Rough sets: past, present, and future , 2018, Natural Computing.

[16]  P. Klenerman,et al.  CD161 Defines a Functionally Distinct Subset of Pro-Inflammatory Natural Killer Cells , 2018, Front. Immunol..

[17]  Huanhuan Liang,et al.  NMI and IFP35 serve as proinflammatory DAMPs during cellular infection and injury , 2017, Nature Communications.

[18]  A. Kikuchi,et al.  The Dickkopf1‐cytoskeleton‐associated protein 4 axis creates a novel signalling pathway and may represent a molecular target for cancer therapy , 2017, British journal of pharmacology.

[19]  Shih-Chang Lin,et al.  Analysis of the CD161-expressing cell quantities and CD161 expression levels in peripheral blood natural killer and T cells of systemic lupus erythematosus patients , 2017, Clinical and Experimental Medicine.

[20]  P. Gregersen,et al.  Molecular signatures in systemic lupus erythematosus: distinction between disease flare and infection , 2016, Lupus Science & Medicine.

[21]  Virginia Pascual,et al.  Personalized Immunomonitoring Uncovers Molecular Networks that Stratify Lupus Patients , 2016, Cell.

[22]  Mark Ellisman,et al.  NF-κB Restricts Inflammasome Activation via Elimination of Damaged Mitochondria , 2016, Cell.

[23]  Eric E. Schadt,et al.  variancePartition: interpreting drivers of variation in complex gene expression studies , 2016, BMC Bioinformatics.

[24]  G. Tsokos,et al.  T Cell Transcriptomes Describe Patient Subtypes in Systemic Lupus Erythematosus , 2015, PloS one.

[25]  Jie Tan,et al.  Big Data Bioinformatics , 2014, Journal of cellular physiology.

[26]  A. Postlethwaite,et al.  Chance, genetics, and the heterogeneity of disease and pathogenesis in systemic lupus erythematosus , 2014, Seminars in Immunopathology.

[27]  T. Vyse,et al.  Autophagy is activated in systemic lupus erythematosus and required for plasmablast development , 2014, Annals of the rheumatic diseases.

[28]  Andreas Radbruch,et al.  Cell-Specific Type I IFN Signatures in Autoimmunity and Viral Infection: What Makes the Difference? , 2013, PloS one.

[29]  Debasis Panda,et al.  Interferon-Inducible Protein IFI35 Negatively Regulates RIG-I Antiviral Signaling and Supports Vesicular Stomatitis Virus Replication , 2013, Journal of Virology.

[30]  F. Maloberti,et al.  What Makes the Difference? , 2013, IEEE Solid-State Circuits Magazine.

[31]  C. Putterman,et al.  Systemic Lupus Erythematosus , 2012, Clinical & developmental immunology.

[32]  Jonathan M. Garibaldi,et al.  Using Rule-Based Machine Learning for Candidate Disease Gene Prioritization and Sample Classification of Cancer Gene Expression Data , 2012, PloS one.

[33]  Guangchuang Yu,et al.  clusterProfiler: an R package for comparing biological themes among gene clusters. , 2012, Omics : a journal of integrative biology.

[34]  L. Truedsson,et al.  Genetic association of miRNA-146a with systemic lupus erythematosus in Europeans through decreased expression of the gene , 2012, Genes and Immunity.

[35]  Gerald McGwin,et al.  Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus. , 2012, Arthritis and rheumatism.

[36]  S. Kamphuis,et al.  Prevalence and burden of pediatric-onset systemic lupus erythematosus , 2010, Nature Reviews Rheumatology.

[37]  N. Olsen,et al.  Interferon signature gene expression is correlated with autoantibody profiles in patients with incomplete lupus syndromes , 2010, Clinical and experimental immunology.

[38]  Marta E Alarcón-Riquelme,et al.  Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci , 2008, Nature Genetics.

[39]  B. Denecke,et al.  IFP 35 is an interferon-induced leucine zipper protein that undergoes interferon-regulated cellular redistribution. , 1994, The Journal of biological chemistry.

[40]  D. Sackett,et al.  Derivation of the SLEDAI. A disease activity index for lupus patients. The Committee on Prognosis Studies in SLE. , 1992, Arthritis and rheumatism.

[41]  Jan Komorowski,et al.  Learning Rule-Based Models - The Rough Set Approach , 2014 .

[42]  Anders Brahme,et al.  Comprehensive biomedical physics , 2014 .

[43]  Theresa Beaubouef,et al.  Rough Sets , 2009, Database Technologies: Concepts, Methodologies, Tools, and Applications.

[44]  D. Holdstock.  Past, present--and future? , 2005, Medicine, conflict, and survival.

[45]  N. Weizman,et al.  Melatonin inhibits nuclear factor kappa B activation and oxidative stress and protects against thioacetamide induced liver damage in rats. , 2004, Journal of hepatology.

[46]  Andrew E. Jaffe,et al.  Bioinformatics Applications Note Gene Expression the Sva Package for Removing Batch Effects and Other Unwanted Variation in High-throughput Experiments , 2022 .

[47]  Jan Komorowski,et al.  BIOINFORMATICS ORIGINAL PAPER doi:10.1093/bioinformatics/btm486 Data and text mining Monte Carlo , 2022 .