Advanced literature analysis in a Big Data world

Annals of the New York Academy of Sciences

Volumn 1387, Issue 1, 2017, Pages 25-33

  Cheadle, Chris ^a,b   Cao, Hongbao ^a   Kalinin, Andrey ^a   Hodgkinson, Jaqui ^a  

^a R&D Solutions ^*  (United States)

^b JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

literature analysis; literature data mining; natural language processing; Pathway Studio

Indexed keywords

BIOLOGICAL MARKER;

ARTICLE; BRAIN REGION; DATA ANALYSIS; DATA EXTRACTION; DATA MINING; HUMAN; INFORMATION; INFORMATION RETRIEVAL; KNOWLEDGE BASE; MEDICAL LITERATURE; MENTAL DISEASE; NATURAL LANGUAGE PROCESSING; NEUROSCIENCE; SCIENTIFIC LITERATURE; SOFTWARE; TAXONOMY; ANIMAL; ANXIETY DISORDERS; BIBLIOGRAPHIC DATABASE; BIOLOGY; BIPOLAR DISORDER; CLASSIFICATION; DATABASE MANAGEMENT SYSTEM; DEPRESSIVE DISORDER, MAJOR; DOCUMENTATION; MASS SCREENING; MEDICAL RESEARCH; MENTAL DISORDERS; METABOLISM; NATIONAL HEALTH ORGANIZATION; PROCEDURES; PROGNOSIS; PUBLICATION; SCHIZOPHRENIA; TRANSLATIONAL RESEARCH; TRENDS; UNITED STATES;

ABSTRACTING AND INDEXING AS TOPIC; ANIMALS; ANXIETY DISORDERS; BIOMARKERS; BIOMEDICAL RESEARCH; BIPOLAR DISORDER; COMPUTATIONAL BIOLOGY; DATA MINING; DATABASE MANAGEMENT SYSTEMS; DATABASES, BIBLIOGRAPHIC; DEPRESSIVE DISORDER, MAJOR; HUMANS; MASS SCREENING; MENTAL DISORDERS; NATIONAL INSTITUTE OF MENTAL HEALTH (U.S.); NATURAL LANGUAGE PROCESSING; PERIODICALS AS TOPIC; PROGNOSIS; SCHIZOPHRENIA; SOFTWARE; TRANSLATIONAL MEDICAL RESEARCH; UNITED STATES;

EID: 85003520650     PISSN: 00778923     EISSN: 17496632     Source Type: Journal    
DOI: 10.1111/nyas.13270     Document Type: Article

References (18)

1. Nikitin, A., S. Egorov, N. Daraselia & I. Mazo. 2003. Pathway studio—the analysis and navigation of molecular networks. Bioinformatics 19: 2155–2157.
2. Rindflesch, T.C., L. Tanabe, J.N. Weinstein & L. Hunter. 2015. EDGAR: extraction of drugs, genes and relations from the biomedical literature. Pac. Symp. Biocomput. 2000: 517–258.
3. Novichkova, S., S. Egorov & N. Daraselia. 2003. MedScan, a natural language processing engine for MEDLINE abstracts. Bioinformatics 19: 1699–1706.
4. Egorov, S., A. Yuryev & N. Daraselia. 2004. A simple and practical dictionary-based approach for identification of proteins in Medline abstracts. J. Am. Med. Inform. Assoc. 11: 174–178.
5. Percha, B. & R.B. Altman. 2015. Learning the structure of biomedical relationships from unstructured text. PLoS Comput. Biol. 11: e1004216.
6. Hettne, K.M., M. Thompson, H.H. van Haagen, et al. 2016. The implicitome: a resource for rationalizing gene–disease associations. PLoS One 11: e0149621.
7. Carpenter, W.T. 2013. RDoC and DSM-5: what's the fuss? Schizophr. Bull. 39: 945–946.
8. Cairelli, M.J., M. Fiszman, H. Zhang & T.C. Rindflesch. 2015. Networks of neuroinjury semantic predications to identify biomarkers for mild traumatic brain injury. J. Biomed. Semantics 6: 25.
9. Research on Biomarkers for Mental Disorders. 2009. National Advisory Mental Health Council (NAMHC) concept clearance. February 13, 2009. Accessed November 17, 2015. http://www.nimh.nih.gov/funding/grant-writing-and-application-process/concept-clearances/2009/research-on-biomarkers-for-mental-disorders.shtml
10. Behaviorism and Mental Health. 2013. Transforming diagnosis: the Thomas Insel article. April 29, 2013. Accessed November 18, 2015. http://behaviorismandmentalhealth.com/2013/05/05/transforming-diagnosis-the-thomas-insel-article//.
11. Huang, D.W., B.T. Sherman & R.A. Lempicki. 2009. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37: 1–13.
12. 452 is associated with psychotic features in bipolar disorder type 1, and with increased CSF KYNA level and reduced KMO expression. Mol. Psychiatry 19: 334–341.
13. Wonodi, I., R.P. McMahon, N. Krishna, et al. 2014. Influence of kynurenine 3-monooxygenase (KMO) gene polymorphism on cognitive function in schizophrenia. Schizophr. Res. 160: 80–87.
14. Yoshimasu, K., K. Mure, M. Hashimoto, et al. 2015. Genetic alcohol sensitivity regulated by ALDH2 and ADH1B polymorphisms is strongly associated with depression and anxiety in Japanese employees. Drug Alcohol Depend. 147: 130–136.
15. Beveridge, N.J. & M.J. Cairns. 2012. MicroRNA dysregulation in schizophrenia. Neurobiol. Dis. 46: 263–271.
16. Watanabe, Y., Y. Iijima, J. Egawa, et al. 2013. Replication in a Japanese population that a MIR30E gene variation is associated with schizophrenia. Schizophr. Res. 150: 596–597.
17. Sun, X.Y., J. Lu, L. Zhang, et al. 2015. Aberrant microRNA expression in peripheral plasma and mononuclear cells as specific blood-based biomarkers in schizophrenia patients. J. Clin. Neurosci. 22: 570–574.
18. Song, H.T., X.Y. Sun, L. Zhang, et al. 2014. A preliminary analysis of association between the down-regulation of microRNA-181b expression and symptomatology improvement in schizophrenia patients before and after antipsychotic treatment. J. Psychiatr. Res. 54: 134–140.