{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:52:06Z","timestamp":1754157126620,"version":"3.41.2"},"reference-count":36,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2009,11,20]],"date-time":"2009-11-20T00:00:00Z","timestamp":1258675200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,11,20]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to demonstrate how the information extracted from scientific text can be directly used in support of life science research projects. In modern digital\u2010based research and academic libraries, librarians should be able to support data discovery and organization of digital entities in order to foster research projects effectively; thus the paper aims to speculate that text mining and knowledge discovery tools could be of great assistance to librarians. Such tools simply enable librarians to overcome increasing complexity in the number as well as contents of scientific literature, especially in the emerging interdisciplinary fields of science. This paper seeks to present an example of how evidences extracted from scientific literature can be directly integrated into <jats:italic>in silico<\/jats:italic> disease models in support of drug discovery projects.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>The application of text\u2010mining as well as knowledge discovery tools is explained in the form of a knowledge\u2010based workflow for drug target candidate identification. Moreover, an <jats:italic>in silico<\/jats:italic> experimentation framework is proposed for the enhancement of efficiency and productivity in the early steps of the drug discovery workflow.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>The <jats:italic>in silico<\/jats:italic> experimentation workflow has been successfully applied to searching for hit and lead compounds in the World\u2010wide <jats:italic>In Silico<\/jats:italic> Docking On Malaria (WISDOM) project and to finding novel inhibitor candidates.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>Direct extraction of biological information from text will ease the task of librarians in managing digital objects and supporting research projects. It is expected that textual data will play an increasingly important role in evidence\u2010based approaches taken by biomedical and translational researchers.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The proposed approach provides a practical example for the direct integration of text\u2010 and knowledge\u2010based data into life science research projects, with the emphasis on their application by academic and research libraries in support of scientific projects.<\/jats:p><\/jats:sec>","DOI":"10.1108\/07378830911007637","type":"journal-article","created":{"date-parts":[[2009,12,5]],"date-time":"2009-12-05T07:16:49Z","timestamp":1259997409000},"page":"505-519","source":"Crossref","is-referenced-by-count":0,"title":["Direct use of information extraction from scientific text for modeling and simulation in the life sciences"],"prefix":"10.1108","volume":"27","author":[{"given":"Martin","family":"Hofman\u2010Apitius","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erfan","family":"Younesi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vinod","family":"Kasam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2022021220074138000_b1","doi-asserted-by":"crossref","unstructured":"Banville, D.L. (2006), \u201cMining chemical structural information from the drug literature\u201d, Drug Discovery Today, Vol. 11 No. 1, pp. 35\u201042.","DOI":"10.1016\/S1359-6446(05)03682-2"},{"key":"key2022021220074138000_b2","doi-asserted-by":"crossref","unstructured":"Botstein, D. and Risch, N. (2003), \u201cDiscovering genotypes underlying human phenotypes: past successes for Mendelian disease, future approaches for complex disease\u201d, Nature Genetics, Vol. 33 (Supplement), pp. 228\u201037.","DOI":"10.1038\/ng1090"},{"key":"key2022021220074138000_b3","doi-asserted-by":"crossref","unstructured":"Butcher, E.C., Berg, E.L. and Kunkel, E.J. (2004), \u201cSystems biology in drug discovery\u201d, Nature Biotechnology, Vol. 22, pp. 1253\u20109.","DOI":"10.1038\/nbt1017"},{"key":"key2022021220074138000_b4","doi-asserted-by":"crossref","unstructured":"Chuang, H., Lee, E., Liu, Y., Lee, D. and Ideker, T. (2007), \u201cNetwork\u2010based classification of breast cancer metastasis\u201d, Molecular Systems Biology, Vol. 3, p. 140, available at: www.pubmedcentral.nih.gov\/picrender.fcgi?artid=2063581&blobtype=pdf (accessed 16 April 2009).","DOI":"10.1038\/msb4100180"},{"key":"key2022021220074138000_b5","doi-asserted-by":"crossref","unstructured":"Ergun, A., Lawrence, C.A., Kohanski, M.A., Brennen, T.A. and Collins, J.J. (2007), \u201cA network biology approach to prostate cancer\u201d, Molecular Systems Biology, Vol. 3, p. 82, available at: www.pubmedcentral.nih.gov\/picrender.fcgi?artid=1828752&blobtype=pdf (accessed 16 April 2009).","DOI":"10.1038\/msb4100125"},{"key":"key2022021220074138000_b6","unstructured":"Foster, I. and Kesselman, C. (1999), The Grid: Blueprint for a New Computing Infrastructure, Morgan Kaufmann Publications, San Francisco, CA."},{"key":"key2022021220074138000_b7","unstructured":"Friedrich, C.M., Dach, H., Gattermayer, T. and Engelbrecht, G. (2008), \u201c@neuLink: a service\u2010oriented application for biomedical knowledge discovery\u201d, in Solomonides, T. (Ed.), Global Healthgrid, IOS Press, Amsterdam."},{"key":"key2022021220074138000_b8","doi-asserted-by":"crossref","unstructured":"Goh, K.I., Cusick, M.E., Valle, D., Childs, B., Vidal, M. and Barabasi, A.L. (2007), \u201cThe human disease network\u201d, Proceedings of the National Academy of Sciences of the United States of America, Vol. 104 No. 21, pp. 8685\u201090.","DOI":"10.1073\/pnas.0701361104"},{"key":"key2022021220074138000_b9","doi-asserted-by":"crossref","unstructured":"Hanisch, D., Fundel, K., Mevissen, H.\u2010T., Zimmer, R. and Fluck, J. (2005), \u201cProMiner: organism\u2010specific protein name detection using approximate string matching\u201d, BMC Bioinformatics, Vol. 6, Supplement 1, p. S14, available at: www.biomedcentral.com\/1471\u20102105\/6\/S1\/S14 (accessed 29 May 2009).","DOI":"10.1186\/1471-2105-6-S1-S14"},{"key":"key2022021220074138000_b10","doi-asserted-by":"crossref","unstructured":"Hirschhorn, J.N. and Daly, M.J. (2005), \u201cGenome\u2010wide association studies for common diseases and complex traits\u201d, Nature Reviews. Genetics, Vol. 6, pp. 95\u2010108.","DOI":"10.1038\/nrg1521"},{"key":"key2022021220074138000_b11","doi-asserted-by":"crossref","unstructured":"Hood, L., Heath, J.R., Phelps, M.E. and Lin, B. (2004), \u201cSystems biology and new technologies enable predictive and preventive medicine\u201d, Science, Vol. 306, pp. 640\u20103.","DOI":"10.1126\/science.1104635"},{"key":"key2022021220074138000_b12","doi-asserted-by":"crossref","unstructured":"Hopkins, A.L. (2008), \u201cNetwork pharmacology: the next paradigm in drug discovery\u201d, Nature Chemical Biology, Vol. 4, pp. 682\u201090.","DOI":"10.1038\/nchembio.118"},{"key":"key2022021220074138000_b13","doi-asserted-by":"crossref","unstructured":"Ibison, P., Jacquot, M., Kam, F., Neville, A.G., Simpson, R.W., Tonnelier, C., Venczel, T. and Johnson, A.P. (1993), \u201cChemical literature data extraction: the CliDE project\u201d, Journal of Chemical Information and Computer Sciences, Vol. 33, pp. 338\u201044.","DOI":"10.1021\/ci00013a010"},{"key":"key2022021220074138000_b14","doi-asserted-by":"crossref","unstructured":"Iles, M.M. (2008), \u201cWhat can genome\u2010wide association studies tell us about the genetics of common disease?\u201d, PLoS Genetics, Vol. 4 No. 2, p. e33, available at: www.plosgenetics.org\/article\/info:doi%2F10.1371%2Fjournal.pgen.0040033 (accessed 17 April 2009).","DOI":"10.1371\/journal.pgen.0040033"},{"key":"key2022021220074138000_b15","unstructured":"Jacq, N. (2006), \u201cDemonstration of in silico docking at a large scale on grid infrastructure\u201d, Studies in Health Technology and Informatics, Vol. 120, pp. 155\u20107."},{"key":"key2022021220074138000_b16","doi-asserted-by":"crossref","unstructured":"Jacq, N., Salzemann, J., Legr\u00e9, Y., Reichstadt, M., Jacq, F., Medernach, E., Zimmermann, M., Maa\u00df, A., Sridhar, V., Vinod\u2010Kusam, K., Montagnat, J., Schwichtenberg, H., Hofmann, M. and Breton, V. (2008), \u201cGrid enabled virtual screening against malaria\u201d, Journal of Grid Computing, Vol. 6 No. 1, pp. 29\u201043.","DOI":"10.1007\/s10723-007-9085-5"},{"key":"key2022021220074138000_b17","doi-asserted-by":"crossref","unstructured":"Jensen, L.J., Saric, J. and Bork, P. (2006), \u201cLiterature mining for the biologist: from information retrieval to biological discovery\u201d, Nature Reviews. Genetics, Vol. 7, pp. 119\u201029.","DOI":"10.1038\/nrg1768"},{"key":"key2022021220074138000_b19","unstructured":"Kasam, V., Salzemann, J., Jacq, N., Mass, A. and Breton, V. (2007b), \u201cLarge scale deployment of molecular docking application on computational grid infrastructures for combating malaria\u201d, in Schulze, B. (Ed.), 7th IEEE International Symposium on Cluster Computing and the Grid: CCGrid 2007, Rio de Janeiro, Brazil, 14\u201017 May 2007, Vol. 2007, IEEE Computer Society, Los Alamitos, CA, pp. 691\u2010700."},{"key":"key2022021220074138000_b18","doi-asserted-by":"crossref","unstructured":"Kasam, V., Zimmermann, M., Maa\u00df, A., Schwichtenberg, H., Wolf, A., Jacq, N., Breton, V. and Hofmann, M. (2007a), \u201cDesign of plasmepsin inhibitors: a virtual high throughput screening approach on the EGEE grid\u201d, Journal of Chemical Information and Modeling, Vol. 47 No. 5, pp. 1818\u201028.","DOI":"10.1021\/ci600451t"},{"key":"key2022021220074138000_b20","doi-asserted-by":"crossref","unstructured":"Kola, I. and Landis, J. (2004), \u201cCan the pharmaceutical industry reduce attrition rates?\u201d, Nature Reviews. Drug Discovery, Vol. 3, pp. 711\u201016.","DOI":"10.1038\/nrd1470"},{"key":"key2022021220074138000_b21","doi-asserted-by":"crossref","unstructured":"Konagaya, A. (2006), \u201cTrends in life science grid: from computing grid to knowledge grid\u201d, BMC Bioinformatics, Vol. 7, Supplement 5, p. S10, available at: www.biomedcentral.com\/content\/pdf\/1471\u20102105\u20107\u2010S5\u2010S10.pdf\/ (accessed 8 April 2009).","DOI":"10.1186\/1471-2105-7-S5-S10"},{"key":"key2022021220074138000_b22","unstructured":"Kotzin, S. (2005), \u201cJournal selection for Medline\u201d, 71st IFLA General Conference and Council: Libraries \u2013 A Voyage of Discovery, Oslo, Norway, August 14\u201018 2005, available at: www.ifla.org\/IV\/ifla71\/papers\/174e\u2010Kotzin.pdf (accessed 17 April 2009)."},{"key":"key2022021220074138000_b23","doi-asserted-by":"crossref","unstructured":"Krallinger, M., Erhardt, R.A. and Valencia, A. (2005), \u201c\u201cText\u2010mining approaches in molecular biology and biomedicine\u201d, Drug Discovery Today, Vol. 10 No. 6, pp. 439\u201045.","DOI":"10.1016\/S1359-6446(05)03376-3"},{"key":"key2022021220074138000_b24","doi-asserted-by":"crossref","unstructured":"Kruglyak, L. and Nickerson, D.A. (2001), \u201c\u201cVariation is the spice of life\u201d, Nature Genetics, Vol. 27, pp. 234\u20106.","DOI":"10.1038\/85776"},{"key":"key2022021220074138000_b25","unstructured":"Lafferty, J., McCallum, A. and Pereira, F. (2001), \u201cConditional random fields: probabilistic models for segmenting and labeling sequence data\u201d, in Brodley, C.E. (Ed.), Machine Learning: Proceedings of 18th International Conference (ICML\u20102001), Williams College, June 28\u2010July 1, 2001, Kaufmann, San Francisco, CA."},{"key":"key2022021220074138000_b26","doi-asserted-by":"crossref","unstructured":"Lim, J., Hao, T., Shaw, C., Patel, A.J., Szabo, G., Rual, J.\u2010F., Fisk, C.J., Li, N., Smolyar, A., Hill, D.E., Barabasi, A.\u2010L., Vidal, M. and Zoghbi, H.Y. (2006), \u201cA protein\u2010protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration\u201d, Cell, Vol. 125, pp. 801\u201014.","DOI":"10.1016\/j.cell.2006.03.032"},{"key":"key2022021220074138000_b27","doi-asserted-by":"crossref","unstructured":"Lu, X., Jain, V.V., Finn, P.W. and Perkins, D.L. (2007), \u201cHubs in biological interaction networks exhibit low changes in expression in experimental asthma\u201d, Molecular Systems Biology, Vol. 3, p. 98, available at: www.pubmedcentral.nih.gov\/picrender.fcgi?artid=1865580&blobtype=pdf (accessed 16 April 2009).","DOI":"10.1038\/msb4100138"},{"key":"key2022021220074138000_b29","doi-asserted-by":"crossref","unstructured":"McDaniel, J.R. and Balmuth, J.R. (1992), \u201cKekul\u00e9: OCR \u2013 optical chemical (structure) recognition\u201d, Journal of Chemical Information and Computer Sciences, Vol. 32, pp. 373\u20108.","DOI":"10.1021\/ci00008a018"},{"key":"key2022021220074138000_b28","doi-asserted-by":"crossref","unstructured":"Mack, R. and Hehenberger, M. (2002), \u201cText\u2010based knowledge discovery: search and mining of life\u2010science documents\u201d, Drug Discovery Today, Vol. 7, pp. 89\u201098.","DOI":"10.1016\/S1359-6446(02)02286-9"},{"key":"key2022021220074138000_b30","doi-asserted-by":"crossref","unstructured":"Motulsky, A.G. (2006), \u201cGenetics of complex diseases\u201d, Journal of Zhejiang University. Science B, Vol. 7 No. 2, pp. 167\u20108.","DOI":"10.1631\/jzus.2006.B0167"},{"key":"key2022021220074138000_b31","doi-asserted-by":"crossref","unstructured":"Pujana, M.A., Han, J.D., Starita, L.M., Stevens, K.N., Tewari, M., Ahn, J.S., Rennert, G., Moreno, V., Kirchhoff, T. and Gold, B. (2007), \u201cNetwork modeling links breast cancer susceptibility and centrosome dysfunction\u201d, Nature Genetics, Vol. 39, pp. 1338\u201049.","DOI":"10.1038\/ng.2007.2"},{"key":"key2022021220074138000_b32","doi-asserted-by":"crossref","unstructured":"Rabiner, L.R. (1989), \u201cA tutorial on hidden Markov models and selected applications in speech recognition\u201d, Proceedings of the IEEE, Vol. 77 No. 2, pp. 257\u201086.","DOI":"10.1109\/5.18626"},{"key":"key2022021220074138000_b33","doi-asserted-by":"crossref","unstructured":"Rauwerda, H., Roos, M., Hertzberger, B.O. and Breit, T.M. (2006), \u201cThe promise of a virtual lab in drug discovery\u201d, Drug Discovery Today, Vol. 11 Nos 5\u20106, pp. 228\u201036.","DOI":"10.1016\/S1359-6446(05)03680-9"},{"key":"key2022021220074138000_b34","doi-asserted-by":"crossref","unstructured":"Ruau, D., Kolarik, C., Mevissen, H.\u2010T., M\u00fcller, E., Assent, I., Krieger, R., Seidl, T., Hofman\u2010Apitius, M. and Zenke, M. (2008), \u201cPublic microarray repository semantic annotation with ontologies employing text mining and expression profile correlation\u201d, BMC Bioinformatics, Vol. 9, Supplement 10, p. O5, available at: www.biomedcentral.com\/1471\u20102105\/9\/S10\/O5 (accessed 29 May 2009).","DOI":"10.1186\/1471-2105-9-S10-O5"},{"key":"key2022021220074138000_b35","unstructured":"Stevens, R., Glover, K., Greenhalgh, C., Jennings, C., Pearce, S., Li, P., Radenkovic, M. and Wipat, A. (2003), \u201cPerforming in silico experiments on the grid: a users perspective\u201d, in Cox, S. (Ed.), Proceedings of UK e\u2010Science All Hands Meeting, Nottingham, 2\u20104 September 2003, EPSRC, Swindon, pp. 43\u201050, available at: www.cs.ncl.ac.uk\/publications\/inproceedings\/papers\/682.pdf (accessed 20 April 2009)."},{"key":"key2022021220074138000_b36","doi-asserted-by":"crossref","unstructured":"Whittaker, P.A. (2004), \u201cThe role of bioinformatics in target validation\u201d, Drug Discovery Today: Technologies, Vol. 1 No. 2, pp. 125\u201033.","DOI":"10.1016\/j.ddtec.2004.08.002"}],"container-title":["Library Hi Tech"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.emeraldinsight.com\/doi\/full-xml\/10.1108\/07378830911007637","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/07378830911007637\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/07378830911007637\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T23:33:36Z","timestamp":1753400016000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/lht\/article\/27\/4\/505-519\/266345"}},"subtitle":[],"editor":[{"given":"M.","family":"H\u00f6ppner","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2009,11,20]]},"references-count":36,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2009,11,20]]}},"alternative-id":["10.1108\/07378830911007637"],"URL":"https:\/\/doi.org\/10.1108\/07378830911007637","relation":{},"ISSN":["0737-8831"],"issn-type":[{"type":"print","value":"0737-8831"}],"subject":[],"published":{"date-parts":[[2009,11,20]]}}}