Systems biology approaches for discovering biomarkers for traumatic brain injury.
暂无分享,去创建一个
Jaques Reifman | Chenggang Yu | Bhaskar Dutta | Xueping Yu | J. Reifman | F. Tortella | J. Feala | J. Dave | Xueping Yu | Bhaskar Dutta | M. AbdulHameed | Chenggang Yu | Kara E. Schmid | Mohamed Diwan M Abdulhameed | Jacob D Feala | Kara Schmid | Jitendra Dave | Frank Tortella
[1] P. Davies,et al. c-Abl in Neurodegenerative Disease , 2011, Journal of Molecular Neuroscience.
[2] T. Ideker,et al. Supporting Online Material for A Systems Approach to Mapping DNA Damage Response Pathways , 2006 .
[3] Christopher M. Overall,et al. Deciphering complex mechanisms in neurodegenerative diseases: the advent of systems biology , 2009, Trends in Neurosciences.
[4] Richard M. Karp,et al. DEGAS: De Novo Discovery of Dysregulated Pathways in Human Diseases , 2010, PloS one.
[5] K. Becker,et al. The Genetic Association Database , 2004, Nature Genetics.
[6] J. Ponsford,et al. Impact of early intervention on outcome after mild traumatic brain injury in children. , 2001, Pediatrics.
[7] Jaques Reifman,et al. Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets* , 2011, Molecular & Cellular Proteomics.
[8] Van,et al. A gene-expression signature as a predictor of survival in breast cancer. , 2002, The New England journal of medicine.
[9] J. Bazarian,et al. The Economic Impact of S-100B as a Pre-Head CT Screening Test on Emergency Department Management of Adult Patients with Mild Traumatic Brain Injury , 2009 .
[10] P. Kochanek,et al. Promising strategies to minimize secondary brain injury after head trauma , 2003, Critical care medicine.
[11] Li Wang,et al. CGI: a new approach for prioritizing genes by combining gene expression and protein-protein interaction data , 2007, Bioinform..
[12] Mathieu Blanchette,et al. Systematic analysis of the protein interaction network for the human transcription machinery reveals the identity of the 7SK capping enzyme. , 2007, Molecular cell.
[13] M. DePamphilis,et al. HUMAN DISEASE , 1957, The Ulster Medical Journal.
[14] M. Moran,et al. Large-scale mapping of human protein–protein interactions by mass spectrometry , 2007, Molecular systems biology.
[15] M. Daly,et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes , 2003, Nature Genetics.
[16] T. Beems,et al. GFAP and S100B are biomarkers of traumatic brain injury , 2010, Neurology.
[17] T. Mathiesen,et al. Genomic responses in rat cerebral cortex after traumatic brain injury , 2005, BMC Neuroscience.
[18] Firas H Kobeissy,et al. Neuroproteomics and systems biology‐based discovery of protein biomarkers for traumatic brain injury and clinical validation , 2008, Proteomics. Clinical applications.
[19] Trey Ideker,et al. Hot spots for modulating toxicity identified by genomic phenotyping and localization mapping. , 2004, Molecular cell.
[20] F. Tortella,et al. Characterization of a new rat model of penetrating ballistic brain injury. , 2005, Journal of neurotrauma.
[21] A. Ottens,et al. High‐capacity peptide‐centric platform to decode the proteomic response to brain injury , 2012, Electrophoresis.
[22] Jaques Reifman,et al. Evidence of probabilistic behaviour in protein interaction networks , 2008, BMC Systems Biology.
[23] T. Leino,et al. Effects of head and extracranial injuries on serum protein S100B levels in trauma patients. , 2004, The Journal of trauma.
[24] F. Tortella,et al. Detection of protein biomarkers using high-throughput immunoblotting following focal ischemic or penetrating ballistic-like brain injuries in rats , 2008, Brain injury.
[25] Jing Zhao,et al. Biomarkers for the diagnosis, prognosis, and evaluation of treatment efficacy for traumatic brain injury , 2011, Neurotherapeutics.
[26] P. Dash,et al. Biomarkers in the clinical diagnosis and management of traumatic brain injury. , 2008, Molecular diagnosis & therapy.
[27] Maqc Consortium. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements , 2006, Nature Biotechnology.
[28] A. Roses,et al. Identification of plasma biomarkers of TBI outcome using proteomic approaches in an APOE mouse model. , 2012, Journal of neurotrauma.
[29] B. Snel,et al. Comparative assessment of large-scale data sets of protein–protein interactions , 2002, Nature.
[30] Korbinian Strimmer,et al. BMC Bioinformatics BioMed Central Methodology article A general modular framework for gene set enrichment analysis , 2009 .
[31] R. Sharan,et al. Expander: from expression microarrays to networks and functions , 2010, Nature Protocols.
[32] Jaques Reifman,et al. Probing the Extent of Randomness in Protein Interaction Networks , 2008, PLoS Comput. Biol..
[33] C. Borlongan,et al. Genetic and histologic evidence implicates role of inflammation in traumatic brain injury-induced apoptosis in the rat cerebral cortex following moderate fluid percussion injury , 2010, Neuroscience.
[34] E. Diamandis,et al. Strategies for discovering novel cancer biomarkers through utilization of emerging technologies , 2008, Nature Clinical Practice Oncology.
[35] Tobias Müller,et al. Identifying functional modules in protein–protein interaction networks: an integrated exact approach , 2008, ISMB.
[36] T. Werner. Bioinformatics applications for pathway analysis of microarray data. , 2008, Current opinion in biotechnology.
[37] Jason A. Papin,et al. Metabolic pathways in the post-genome era. , 2003, Trends in biochemical sciences.
[38] Sebastian Bernhardsson,et al. The Blind Watchmaker Network: Scale-Freeness and Evolution , 2008, PloS one.
[39] Alexander R. Pico,et al. WikiPathways: Pathway Editing for the People , 2008, PLoS biology.
[40] R. Aebersold,et al. Mass spectrometry-based proteomics , 2003, Nature.
[41] Carl W. Cotman,et al. Axonal mRNA in Uninjured and Regenerating Cortical Mammalian Axons , 2009, The Journal of Neuroscience.
[42] A. Gabrielli,et al. Clinical Utility of Serum Levels of Ubiquitin C-terminal Hydrolase as a Biomarker for Severe Traumatic Brain Injury , 2022 .
[43] C. Landry,et al. An in Vivo Map of the Yeast Protein Interactome , 2008, Science.
[44] R. Sharan,et al. Protein networks in disease. , 2008, Genome research.
[45] P. Dash,et al. Human traumatic brain injury alters plasma microRNA levels. , 2010, Journal of neurotrauma.
[46] Michael L. Creech,et al. Integration of biological networks and gene expression data using Cytoscape , 2007, Nature Protocols.
[47] B. Golomb,et al. Prevalence and Psychological Correlates of Traumatic Brain Injury in Operation Iraqi Freedom , 2010, The Journal of head trauma rehabilitation.
[48] H. Lehrach,et al. A Human Protein-Protein Interaction Network: A Resource for Annotating the Proteome , 2005, Cell.
[49] T. Speed,et al. Neuron-Specific mRNA Complexity Responses during Hippocampal Apoptosis after Traumatic Brain Injury , 2004, The Journal of Neuroscience.
[50] J. Carazo,et al. GENECODIS: a web-based tool for finding significant concurrent annotations in gene lists , 2007, Genome Biology.
[51] F. Tortella,et al. Novel Differential Neuroproteomics Analysis of Traumatic Brain Injury in Rats* , 2006, Molecular & Cellular Proteomics.
[52] Benno Schwikowski,et al. Discovering regulatory and signalling circuits in molecular interaction networks , 2002, ISMB.
[53] N. Friedman,et al. Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells , 2011, Nature Biotechnology.
[54] F. Tortella,et al. P43/pro-EMAPII: a potential biomarker for discriminating traumatic versus ischemic brain injury. , 2009, Journal of Neurotrauma.
[55] John Q. Trojanowski,et al. Alzheimer's pathology in human temporal cortex surgically excised after severe brain injury , 2004, Experimental Neurology.
[56] Jaques Reifman,et al. PathNet: a tool for pathway analysis using topological information , 2012, Source Code for Biology and Medicine.
[57] T. Ideker,et al. A new approach to decoding life: systems biology. , 2001, Annual review of genomics and human genetics.
[58] F. Tortella,et al. Elevated levels of serum glial fibrillary acidic protein breakdown products in mild and moderate traumatic brain injury are associated with intracranial lesions and neurosurgical intervention. , 2012, Annals of emergency medicine.
[59] Ziv Bar-Joseph,et al. Biological interaction networks are conserved at the module level , 2011, BMC Systems Biology.
[60] R. Bullock,et al. Glial neuronal ratio: a novel index for differentiating injury type in patients with severe traumatic brain injury. , 2012, Journal of neurotrauma.
[61] T. Ideker,et al. Network-based classification of breast cancer metastasis , 2007, Molecular systems biology.
[62] B. Jordan,et al. Chronic Traumatic Brain Injury Associated with Boxing , 2000, Seminars in neurology.
[63] Yoshihiro Yamanishi,et al. KEGG for linking genomes to life and the environment , 2007, Nucleic Acids Res..
[64] A. Barabasi,et al. The human disease network , 2007, Proceedings of the National Academy of Sciences.
[65] J. Foekens,et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer , 2005, The Lancet.
[66] T. Liu,et al. Toward an understanding of the protein interaction network of the human liver , 2011, Molecular systems biology.
[67] Joshua M. Stuart,et al. A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules , 2003, Science.
[68] P. Kochanek,et al. Conventional and functional proteomics using large format two-dimensional gel electrophoresis 24 hours after controlled cortical impact in postnatal day 17 rats. , 2002, Journal of neurotrauma.
[69] S. Kasif,et al. Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models , 2007, PLoS genetics.
[70] Alex Matter,et al. Glivec (STI571, imatinib), a rationally developed, targeted anticancer drug , 2002, Nature Reviews Drug Discovery.
[71] J. Ioannidis,et al. Comparison of effect sizes associated with biomarkers reported in highly cited individual articles and in subsequent meta-analyses. , 2011, JAMA.
[72] James R. Knight,et al. A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae , 2000, Nature.
[73] Brad T. Sherman,et al. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.
[74] J. Hutchison,et al. Biomarkers and diagnosis; protein biomarkers in serum of pediatric patients with severe traumatic brain injury identified by ICAT-LC-MS/MS. , 2007, Journal of neurotrauma.
[75] T. Beems,et al. Glial and neuronal proteins in serum predict outcome after severe traumatic brain injury , 2004, Neurology.
[76] D. Hovda,et al. Molecular and Physiological Responses to Juvenile Traumatic Brain Injury: Focus on Growth and Metabolism , 2010, Developmental Neuroscience.
[77] A. Barabasi,et al. High-Quality Binary Protein Interaction Map of the Yeast Interactome Network , 2008, Science.
[78] R. Ozawa,et al. A comprehensive two-hybrid analysis to explore the yeast protein interactome , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[79] J. Powell,et al. Accuracy of mild traumatic brain injury diagnosis. , 2008, Archives of physical medicine and rehabilitation.
[80] H. Thompson,et al. Experimental models of traumatic brain injury: Do we really need to build a better mousetrap? , 2005, Neuroscience.
[81] Pablo Tamayo,et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[82] J. Hutchison,et al. Protein Biomarkers in Serum of Pediatric Patients with Severe Traumatic Brain Injury Identified by ICAT–LC-MS/MS , 2007 .
[83] J. Brisman,et al. Reliability of S100B in predicting severity of central nervous system injury , 2007, Neurocritical care.
[84] Joshua M. Stuart,et al. Conserved Genetic Modules 5 / 29 / 2003 1 A gene co-expression network for global discovery of conserved genetic modules in H . sapiens , D . melanogaster , C . elegans , and S . cerevisiae , 2003 .
[85] Jackson Streeter,et al. Blood-based diagnostics of traumatic brain injuries , 2011, Expert review of molecular diagnostics.
[86] Jaques Reifman,et al. A Novel Scoring Approach for Protein Co-Purification Data Reveals High Interaction Specificity , 2009, PLoS Comput. Biol..
[87] A. Barabasi,et al. Drug—target network , 2007, Nature Biotechnology.
[88] Francisco Tirado,et al. GeneCodis: interpreting gene lists through enrichment analysis and integration of diverse biological information , 2009, Nucleic Acids Res..
[89] S. Marshall,et al. Association between Recurrent Concussion and Late-Life Cognitive Impairment in Retired Professional Football Players , 2005, Neurosurgery.
[90] Trey Ideker,et al. Building with a scaffold: emerging strategies for high- to low-level cellular modeling. , 2003, Trends in biotechnology.
[91] Ioannis Xenarios,et al. Network-Guided Analysis of Genes with Altered Somatic Copy Number and Gene Expression Reveals Pathways Commonly Perturbed in Metastatic Melanoma , 2011, PloS one.
[92] B. Romner,et al. Can Low Serum Levels of S100B Predict Normal CT Findings After Minor Head Injury in Adults?: An Evidence‐Based Review and Meta‐Analysis , 2010, The Journal of head trauma rehabilitation.
[93] C. Kavalci,et al. The value of serum tau protein for the diagnosis of intracranial injury in minor head trauma. , 2007, The American journal of emergency medicine.
[94] P. Dash,et al. High‐density microarray analysis of hippocampal gene expression following experimental brain injury , 2002, Journal of neuroscience research.
[95] D. Kell,et al. Here is the evidence, now what is the hypothesis? The complementary roles of inductive and hypothesis-driven science in the post-genomic era. , 2004, BioEssays : news and reviews in molecular, cellular and developmental biology.
[96] J. Ponsford,et al. Impact of early intervention on outcome following mild head injury in adults , 2002, Journal of neurology, neurosurgery, and psychiatry.
[97] B. Stoica,et al. Gene expression profile changes are commonly modulated across models and species after traumatic brain injury. , 2003, Journal of neurotrauma.
[98] E. Jauch,et al. C-tau biomarker of neuronal damage in severe brain injured patients: association with elevated intracranial pressure and clinical outcome , 2002, Brain Research.
[99] Pooja Mittal,et al. A novel signaling pathway impact analysis , 2009, Bioinform..
[100] Lincoln Stein,et al. Reactome: a database of reactions, pathways and biological processes , 2010, Nucleic Acids Res..
[101] B. Palsson,et al. The model organism as a system: integrating 'omics' data sets , 2006, Nature Reviews Molecular Cell Biology.
[102] T. Ideker,et al. Modeling cellular machinery through biological network comparison , 2006, Nature Biotechnology.
[103] Pei Wang,et al. Gene expression profiling of peripheral blood leukocytes identifies and validates ABCB1 as a novel biomarker for Alzheimer's disease , 2011, Neurobiology of Disease.
[104] E. Braunwald,et al. Ability of minor elevations of troponins I and T to predict benefit from an early invasive strategy in patients with unstable angina and non-ST elevation myocardial infarction: results from a randomized trial. , 2001, JAMA.
[105] F. Tortella,et al. Neuronal and glial markers are differently associated with computed tomography findings and outcome in patients with severe traumatic brain injury: a case control study , 2011, Critical care.
[106] T. Kaneko,et al. Serum glial fibrillary acidic protein is a highly specific biomarker for traumatic brain injury in humans compared with S-100B and neuron-specific enolase. , 2010, The Journal of trauma.
[107] A. Gabrielli,et al. Biokinetic analysis of ubiquitin C-terminal hydrolase-L1 (UCH-L1) in severe traumatic brain injury patient biofluids. , 2011, Journal of neurotrauma.
[108] A. Barabasi,et al. An empirical framework for binary interactome mapping , 2008, Nature Methods.
[109] R. Anderson,et al. High serum S100B levels for trauma patients without head injuries. , 2001, Neurosurgery.
[110] H. Weng,et al. Tau proteins in serum predict outcome after severe traumatic brain injury. , 2010, The Journal of surgical research.
[111] S. L. Wong,et al. Towards a proteome-scale map of the human protein–protein interaction network , 2005, Nature.
[112] Jaques Reifman,et al. Inferring high-confidence human protein-protein interactions , 2012, BMC Bioinformatics.
[113] V. Mathura,et al. Genomic analysis of response to traumatic brain injury in a mouse model of Alzheimer's disease (APPsw) , 2007, Brain Research.
[114] Hanlee P. Ji,et al. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. , 2006, Nature biotechnology.
[115] R. Aebersold,et al. Applying mass spectrometry-based proteomics to genetics, genomics and network biology , 2009, Nature Reviews Genetics.
[116] S. DeKosky,et al. Traumatic brain injury: football, warfare, and long-term effects. , 2010, Minnesota medicine.
[117] Antonio Belli,et al. Transcriptomics of traumatic brain injury: gene expression and molecular pathways of different grades of insult in a rat organotypic hippocampal culture model. , 2010, Journal of neurotrauma.
[118] A. Faden,et al. Neuroprotection for traumatic brain injury: translational challenges and emerging therapeutic strategies. , 2010, Trends in pharmacological sciences.
[119] G. Pasinetti,et al. From proteomics to biomarker discovery in Alzheimer's disease , 2005, Brain Research Reviews.
[120] Doheon Lee,et al. Inferring Pathway Activity toward Precise Disease Classification , 2008, PLoS Comput. Biol..
[121] A. Gabrielli,et al. Ubiquitin C-terminal hydrolase is a novel biomarker in humans for severe traumatic brain injury* , 2010, Critical care medicine.
[122] Ron Shamir,et al. Identification of functional modules using network topology and high-throughput data , 2007, BMC Systems Biology.
[123] C. Werner,et al. Pathophysiology of traumatic brain injury. , 2007, British journal of anaesthesia.
[124] Arun K. Ramani,et al. Protein interaction networks from yeast to human. , 2004, Current opinion in structural biology.
[125] Rainer Breitling,et al. Graph-based iterative Group Analysis enhances microarray interpretation , 2004, BMC Bioinformatics.
[126] A. Barabasi,et al. Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.
[127] Bart De Moor,et al. BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis , 2005, Bioinform..
[128] A. Gabrielli,et al. αII-spectrin breakdown products (SBDPs): diagnosis and outcome in severe traumatic brain injury patients. , 2010, Journal of neurotrauma.
[129] Peter Uetz,et al. Benchmarking yeast two‐hybrid systems using the interactions of bacterial motility proteins , 2009, Proteomics.