Can literature analysis identify innovation drivers in drug discovery?

Maps of random walks on complex networks reveal community structure

Rosvall, M., & Bergstrom, C. T. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0706851105 · Cited by 4,583 · see citing works

Little Science, Big Science

Price, D. J. D. S. (1963) · Columbia University Press eBooks · doi:10.7312/pric91844 · Cited by 4,340 · see citing works

An Antidiabetic Thiazolidinedione Is a High Affinity Ligand for Peroxisome Proliferator-activated Receptor γ (PPARγ)

Lehmann, J. M., Moore, L. B., Smith-Oliver, T. A., Wilkison, W. O., Willson, T. M., & Kliewer, S. A. (1995) · Journal of Biological Chemistry · doi:10.1074/jbc.270.22.12953 · Cited by 3,626 · see citing works

Networks of Scientific Papers

Price, D. J. D. S. (1965) · Science · doi:10.1126/science.149.3683.510 · Cited by 3,121 · see citing works

Drugs for bad bugs: confronting the challenges of antibacterial discovery

Payne, D. J., Gwynn, M. N., Holmes, D. J., & Pompliano, D. L. (2007) · Nature Reviews Drug Discovery · doi:10.1038/nrd2201 · Cited by 2,512 · see citing works

Time Series Analysis and Its Applications

Shumway, R. H., & Stoffer, D. S. (2010) · Springer texts in statistics · doi:10.1007/978-1-4419-7865-3 · Cited by 2,015 · see citing works

Untitled work

(2007) · Cited by 1,133 · see citing works

A well adapted regulatory contrivance: regulatory T cell development and the forkhead family transcription factor Foxp3

Fontenot, J. D., & Rudensky, A. Y. (2005) · Nature Immunology · doi:10.1038/ni1179 · Cited by 947 · see citing works

Competing on analytics: the new science of winning

(2007) · Choice Reviews Online · doi:10.5860/choice.44-6322 · Cited by 947 · see citing works

The American Association for the Advancement of Science

Haultain, A. (1889) · Nature · doi:10.1038/040556a0 · Cited by 944 · see citing works

Are We Ready for Pandemic Influenza?

Webby, R. J., & Webster, R. G. (2003) · Science · doi:10.1126/science.1090350 · Cited by 659 · see citing works

Measures of semantic similarity and relatedness in the biomedical domain

Ted Pedersen, A., Pakhomov, S., Patwardhan, S., & Chute, C. G. (2006) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2006.06.004 · Cited by 566 · see citing works

Innovation as co-evolution of scientific and technological networks: exploring tissue engineering

Murray, F. (2002) · Research Policy · doi:10.1016/s0048-7333(02)00070-7 · Cited by 511 · see citing works

Journal status

Bollen, J., Rodriquez, M. A., & Herbert Van De Sompel, A. (2006) · Scientometrics · doi:10.1007/s11192-006-0176-z · Cited by 403 · see citing works

Electronic Publication and the Narrowing of Science and Scholarship

Evans, J. A. (2008) · Science · doi:10.1126/science.1150473 · Cited by 364 · see citing works

The politics of publication

Lawrence, P. A. (2003) · Nature · doi:10.1038/422259a · Cited by 354 · see citing works

Thalidomide: current and potential clinical applications

Calabrese, L. H., & Fleischer, A. B. (2000) · The American Journal of Medicine · doi:10.1016/s0002-9343(99)00408-8 · Cited by 327 · see citing works

Time Series Analysis and Its Applications

Shumway, R. H., & Stoffer, D. S. (2006) · Springer eBooks · doi:10.1007/0-387-36276-2 · Cited by 302 · see citing works

The mismeasurement of science

Lawrence, P. A. (2007) · Current Biology · doi:10.1016/j.cub.2007.06.014 · Cited by 296 · see citing works

Going to College to Avoid the Draft: The Unintended Legacy of the Vietnam War

Card, D., & Lemieux, T. (2001) · American Economic Review · doi:10.1257/aer.91.2.97 · Cited by 270 · see citing works

Novel approaches to developing new antibiotics for bacterial infections

Coates, A. R. M., & Hu, Y. (2007) · British Journal of Pharmacology · doi:10.1038/sj.bjp.0707432 · Cited by 218 · see citing works

Relativity of citation performance and excellence measures: From cross-field to cross-scale effects of field-normalisation

Zitt, M., Ramanana-Rahary, S., & Bassecoulard, E. (2005) · Scientometrics · doi:10.1007/s11192-005-0218-y · Cited by 182 · see citing works

Adiponectin and its gene variants as risk factors for insulin resistance, the metabolic syndrome and cardiovascular disease

Gable, D. R., Hurel, S. J., & Humphries, S. E. (2006) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2006.02.010 · Cited by 159 · see citing works

Towards the development of a conceptual distance metric for the UMLS

Caviedes, J. E., & Cimino, J. J. (2004) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2004.02.001 · Cited by 113 · see citing works

Macro trends in pharmaceutical innovation

Cohen, F. J. (2005) · Nature Reviews Drug Discovery · doi:10.1038/nrd1610 · Cited by 111 · see citing works

Coauthorship and Coinventorship

Ducor, P. (2000) · Science · doi:10.1126/science.289.5481.873 · Cited by 103 · see citing works

Literature mining in support of drug discovery

Agarwal, P., & Searls, D. B. (2008) · Briefings in Bioinformatics · doi:10.1093/bib/bbn035 · Cited by 85 · see citing works

The fallacies of hope: will we discover new antibiotics to combat pathogenic bacteria in time?

Vicente, M., Hodgson, J., Massidda, O., Tønjum, T., Henriques‐Normark, B., & Ron, E. Z. (2006) · FEMS Microbiology Reviews · doi:10.1111/j.1574-6976.2006.00038.x · Cited by 72 · see citing works

Structural Disequilibria in Biomedical Research

Teitelbaum, M. S. (2008) · Science · doi:10.1126/science.1160272 · Cited by 71 · see citing works

Novel targets and therapeutic strategies for type 2 diabetes

Morral, N. (2003) · Trends in Endocrinology and Metabolism · doi:10.1016/s1043-2760(03)00031-6 · Cited by 65 · see citing works

Antihypertensive therapies

Smith, R. E. T., & Ashiya, M. (2007) · Nature Reviews Drug Discovery · doi:10.1038/nrd2354 · Cited by 59 · see citing works

Frances Oldham Kelsey: FDA Medical Reviewer Leaves Her Mark on History

Bren, L. (2001) · PsycEXTRA Dataset · doi:10.1037/e542662006-006 · Cited by 58 · see citing works

Non-insulin therapies for type 2 diabetes

Ashiya, M., & Smith, R. E. T. (2007) · Nature Reviews Drug Discovery · doi:10.1038/nrd2420 · Cited by 52 · see citing works

Building Customized Data Pipelines Using the Entrez Programming Utilities (eUtils)

Sayers, E. W., & Wheeler, D. (2004) · Cited by 47 · see citing works

Finding improved medicines: the role of academic–industrial collaboration

Chin-Dusting, J. P. F., Mizrahi, J. L., Jennings, G., & Fitzgerald, D. (2005) · Nature Reviews Drug Discovery · doi:10.1038/nrd1879 · Cited by 46 · see citing works

Financial anatomy of neuroscience research

Dorsey, E. R., Vitticore, P., de Roulet, J., Thompson, J. P., Carrasco, M., Johnston, S. C., Holloway, R. G., & Moses, H. (2006) · Annals of Neurology · doi:10.1002/ana.21047 · Cited by 41 · see citing works

A case study of lean drug discovery: from project driven research to innovation studios and process factories

Ullman, F., & Boutellier, R. (2008) · Drug Discovery Today · doi:10.1016/j.drudis.2008.03.011 · Cited by 40 · see citing works

Why has R&D productivity declined in the pharmaceutical industry?

Ruffolo, R. R., Jr. (2006) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.1.2.99 · Cited by 36 · see citing works

The growth of the cell death field: an analysis from the ISI-Science citation index

Garfield, E., & Melino, G. (1997) · Cell Death and Differentiation · doi:10.1038/sj.cdd.4400261 · Cited by 34 · see citing works

Optimizing the discovery organization for innovation

Sams‐Dodd, F. (2005) · Drug Discovery Today · doi:10.1016/s1359-6446(05)03539-7 · Cited by 29 · see citing works

Human retroviruses in leukaemia and AIDS: reflections on their discovery, biology and epidemiology

Karpas, A. (2004) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1017/s1464793104006505 · Cited by 29 · see citing works

Non-Insulin Dependent Diabetes Mellitus: Present Therapies and New Drug Targets&#

Das, S. K., & Chakrabarti, R. (2005) · Mini-Reviews in Medicinal Chemistry · doi:10.2174/138955705774575273 · Cited by 27 · see citing works

Mining the bibliome

Searls, D. B. (2001) · The Pharmacogenomics Journal · doi:10.1038/sj.tpj.6500030 · Cited by 17 · see citing works

Aggregation properties of relative impact and other classical indicators: Convexity issues and the Yule-Simpson paradox

Ramanana-Rahary, S., Zitt, M., & Rousseau, R. (2009) · Scientometrics · doi:10.1007/s11192-009-0420-4 · Cited by 17 · see citing works

The origins of new drugs

KNELLER, R. W. (2005) · Nature Biotechnology · doi:10.1038/nbt0505-529 · Cited by 16 · see citing works

Drug Discovery and Development in the Age of Molecular Medicine

Vallance, P. J., & Levick, M. P. (2007) · Clinical Pharmacology & Therapeutics · doi:10.1038/sj.clpt.6100333 · Cited by 14 · see citing works

AN ALTERNATIVE TO JOURNAL-BASED IMPACT FACTORS

Takahashi, K., Aw, T. C., & Koh, D. S. Q. (1999) · Occupational Medicine · doi:10.1093/occmed/49.1.57-a · Cited by 14 · see citing works

Trends in biotech literature 2006

Taroncher‐Oldenburg, G., & Marshall, A. (2007) · Nature Biotechnology · doi:10.1038/nbt0907-961 · Cited by 14 · see citing works

Mission possible: managing innovation in drug discovery

Zhong, X., & Moseley, G. B. (2007) · Nature Biotechnology · doi:10.1038/nbt0807-945 · Cited by 13 · see citing works

Where Have All the Dollars Gone?

Cohen, J. (2008) · Science · doi:10.1126/science.321.5888.520 · Cited by 11 · see citing works

New insights into the pathogenesis and treatment of chronic myeloproliferative disorders

Mesa, R. A. (2008) · Current Opinion in Hematology · doi:10.1097/moh.0b013e3282f3debd · Cited by 11 · see citing works

Mining cross-terminology links in the UMLS.

Patel, C. O., & Cimino, J. J. (2006) · PubMed · Cited by 7 · see citing works

Funding impact of the National Cancer Act and beyond.

Kalberer, J. T., & Newell, G. R. (1979) · PubMed · Cited by 5 · see citing works

Automating terminological networks to link heterogeneous biomedical databases.

Wang, X., Quek, H. N., Cantor, M. N., Kra, P., Schultz, A., & Lussier, Y. A. (2004) · PubMed · Cited by 3 · see citing works

Bang for the Buck

Cohen, J. D. (2008) · Science · doi:10.1126/science.321.5888.518 · Cited by 3 · see citing works

QSAR without borders

Muratov, E. N., Bajorath, J., Sheridan, R. P., Tetko, I. V., Filimonov, D., Poroikov, V., Oprea, T. I., Baskin, I. I., Varnek, A., Roitberg, A., et al. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00098a · Cited by 913 · see citing works

Exploiting drug-disease relationships for computational drug repositioning

Dudley, J. T., Deshpande, T. A., & Butte, A. J. (2011) · Briefings in Bioinformatics · doi:10.1093/bib/bbr013 · Cited by 526 · see citing works

Unexplored therapeutic opportunities in the human genome

Oprea, T. I., Bologa, C. G., Brunak, S., Campbell, A., Gan, G. N., Gaulton, A., Gomez, S. M., Guha, R., Hersey, A., Holmes, J., et al. (2018) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2018.14 · Cited by 378 · see citing works

Erratum: Unexplored therapeutic opportunities in the human genome

Oprea, T. I., Bologa, C., Brunak, S., Campbell, A., Gan, G. N., Gaulton, A., Gomez, S. M., Guha, R., Hersey, A., Holmes, J., et al. (2018) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2018.52 · Cited by 304 · see citing works

Information retrieval and text mining technologies for chemistry

Krallinger, M., Rabal, O., Lourenço, A., Oyarzabal, J., & Valencia, A. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00851 · Cited by 281 · see citing works

In silico drug repositioning – what we need to know

Liu, Z., Fang, H., Reagan, K., Xu, X., Mendrick, D. L., Slikker, W., & Tong, W. (2012) · Drug Discovery Today · doi:10.1016/j.drudis.2012.08.005 · Cited by 185 · see citing works

Exploring why global health needs are unmet by research efforts: the potential influences of geography, industry and publication incentives

Yegros, A., van de Klippe, W., García, M. F. A., & Ràfols, I. (2020) · Health Research Policy and Systems · doi:10.1186/s12961-020-00560-6 · Cited by 176 · see citing works

The new Excellence Indicator in the World Report of the SCImago Institutions Rankings 2011

Bornmann, L., Anegón, F. D. M., & Loet Leydesdorff, A. (2012) · Journal of Informetrics · doi:10.1016/j.joi.2011.11.006 · Cited by 165 · see citing works

Medical Semantic Similarity with a Neural Language Model

Vine, L. D., Zuccon, G., Koopman, B., Sitbon, L., & Bruza, P. (2014) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/2661829.2661974 · Cited by 143 · see citing works

Drug discovery in the next decade: innovation needed ASAP

Bennani, Y. L. (2011) · Drug Discovery Today · doi:10.1016/j.drudis.2011.06.004 · Cited by 119 · see citing works

The pace of artificial intelligence innovations: Speed, talent, and trial-and-error

Tang, X., Li, X., Ding, Y., Song, M., & Bu, Y. (2020) · Journal of Informetrics · doi:10.1016/j.joi.2020.101094 · Cited by 115 · see citing works

A bibliometric mapping of the structure of STEM education using co‐word analysis

Assefa, S. G., & Rorissa, A. (2013) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22917 · Cited by 110 · see citing works

Unrealized targets in the discovery of antibiotics for Gram-negative bacterial infections

Theuretzbacher, U., Blasco, B., Duffey, M., & Piddock, L. J. V. (2023) · Nature Reviews Drug Discovery · doi:10.1038/s41573-023-00791-6 · Cited by 102 · see citing works

A Triple Helix Model of Medical Innovation: Supply, Demand, and Technological Capabilities in Terms of Medical Subject Headings

Petersen, A. M., Rotolo, D., & Loet Leydesdorff, A. (2016) · Research Policy · doi:10.1016/j.respol.2015.12.004 · Cited by 93 · see citing works

Research Portfolio Analysis in Science Policy: Moving from Financial Returns to Societal Benefits

Wallace, M. L., & Ràfols, I. (2015) · Minerva · doi:10.1007/s11024-015-9271-8 · Cited by 85 · see citing works

Bibliometric perspectives on medical innovation using the medical subject Headings of P ub M ed

Loet Leydesdorff, A., Rotolo, D., & Ràfols, I. (2012) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22715 · Cited by 83 · see citing works

Funding Data from Publication Acknowledgments: Coverage, Uses, and Limitations

Grassano, N., Rotolo, D., Hutton, J., Lang, F., & Hopkins, M. M. (2017) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23737 · Cited by 75 · see citing works

Institutional Shaping of Research Priorities: A Case Study on Avian Influenza

Wallace, M. L., & Ràfols, I. (2016) · Research Policy · doi:10.1016/j.respol.2018.07.005 · Cited by 61 · see citing works

Mapping Global Research on Ocean Literacy: Implications for Science, Policy, and the Blue Economy

Paredes, E., Mokos, M., Vanreusel, A., & Deprez, T. (2021) · Frontiers in Marine Science · doi:10.3389/fmars.2021.648492 · Cited by 55 · see citing works

The role of translational bioinformatics in drug discovery

Buchan, N. S., Rajpal, D. K., Webster, Y., Alatorre, C., Gudivada, R. C., Zheng, C., Sanséau, P., & Koehler, J. (2011) · Drug Discovery Today · doi:10.1016/j.drudis.2011.03.002 · Cited by 53 · see citing works

Innovation as a nonlinear process, the scientometric perspective, and the specification of an ‘innovation opportunities explorer’

Loet Leydesdorff, A., Rotolo, D., & de Nooy, W. (2013) · Technology Analysis and Strategic Management · doi:10.1080/09537325.2013.801948 · Cited by 50 · see citing works

Cited references and Medical Subject Headings (MeSH) as two different knowledge representations: clustering and mappings at the paper level

Loet Leydesdorff, A., Comins, J. A., Sorensen, A. A., Bornmann, L., & Hellsten, I. (2016) · Scientometrics · doi:10.1007/s11192-016-2119-7 · Cited by 46 · see citing works

The Reporting Items for Patent Landscapes statement

Smith, J. A., Arshad, Z., Trippe, A. P., Collins, P. G. S., Brindley, D. A., & Carr, A. J. (2018) · Nature Biotechnology · doi:10.1038/nbt.4291 · Cited by 45 · see citing works

An evaluation of corpus-driven measures of medical concept similarity for information retrieval

Koopman, B., Zuccon, G., Bruza, P., Sitbon, L., & Lawley, M. (2012) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/2396761.2398661 · Cited by 41 · see citing works

An in silico analysis of microRNAs: Mining the miRNAome

Murray, B. S., Choe, S. E., Woods, M. W., RYAN, T. E., & Liu, W. (2010) · Molecular BioSystems · doi:10.1039/c003961f · Cited by 40 · see citing works

Literature analysis for systematic drug repurposing: a case study from Biovista

Lekka, E., Deftereos, S., Persidis, A., Persidis, A., & Andronis, C. (2011) · Drug Discovery Today Therapeutic Strategies · doi:10.1016/j.ddstr.2011.06.005 · Cited by 37 · see citing works

Research and development in drug innovation: reflections from the 2013 bioeconomy conference in China, lessons learned and future perspectives

Liu, C., Constantinides, P. P., & Li, Y. (2014) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2014.01.002 · Cited by 36 · see citing works

Inferring novel gene-disease associations using Medical Subject Heading Over-representation Profiles

Cheung, W., Ouellette, B. F. F., & Wasserman, W. W. (2012) · Genome Medicine · doi:10.1186/gm376 · Cited by 35 · see citing works

Why commercialization of gene therapy stalled; examining the life cycles of gene therapy technologies

Ledley, F. D., McNamee, L. M., Uzdil, V., & Morgan, I. (2013) · Gene Therapy · doi:10.1038/gt.2013.72 · Cited by 35 · see citing works

Patterns of technological innovation in biotech

McNamee, L. M., & Ledley, F. D. (2012) · Nature Biotechnology · doi:10.1038/nbt.2389 · Cited by 35 · see citing works

Text mining patents for biomedical knowledge

Rodriguez‐Esteban, R., & Bundschus, M. (2016) · Drug Discovery Today · doi:10.1016/j.drudis.2016.05.002 · Cited by 34 · see citing works

A critical analysis of publication trends from 2005–2015 in microwave assisted extraction of botanicals: How far we have come and the road ahead

Mandal, V., & Tandey, R. (2016) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2016.05.020 · Cited by 28 · see citing works

Drug repurposing against Parkinson's disease by text mining the scientific literature

Zhu, Y., Jung, W., Wang, F., & Che, C. (2020) · Library Hi Tech · doi:10.1108/lht-08-2019-0170 · Cited by 28 · see citing works

In silico analysis of molecular mechanisms of legume lectin‐induced apoptosis in cancer cells

Shi, Z., An, N., Zhao, S., Li, X., Bao, J., & Yue, B. (2013) · Cell Proliferation · doi:10.1111/cpr.12009 · Cited by 27 · see citing works

Scientometric Overview in Nanobiodrugs

Konur, O. (2016) · Elsevier eBooks · doi:10.1016/b978-0-323-47347-7.00015-x · Cited by 26 · see citing works

Concept embedding to measure semantic relatedness for biomedical information ontologies

Park, J., Kim, K., Hwang, W., & Lee, D. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103182 · Cited by 26 · see citing works

When Neuroscience Meets Pharmacology: A Neuropharmacology Literature Analysis

Yeung, A. W. K., Tzvetkov, N. T., & Atanasov, A. G. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00852 · Cited by 25 · see citing works

When Cyclodextrins Met Data Science: Unveiling Their Pharmaceutical Applications through Network Science and Text-Mining

Rincón‐López, J., Almanza-Arjona, Y. C., Riascos, A. P., & Rojas-Aguirre, Y. (2021) · Pharmaceutics · doi:10.3390/pharmaceutics13081297 · Cited by 25 · see citing works

Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs)

Cheung, W., Ouellette, B. F. F., & Wasserman, W. W. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-249 · Cited by 25 · see citing works

Empowering industrial research with shared biomedical vocabularies

Harland, L., Larminie, C. G. C., Sansone, S., Popa, S., Marshall, M. S., Braxenthaler, M., Cantor, M. N., Filsell, W., Forster, M. J., Huang, E. S., et al. (2011) · Drug Discovery Today · doi:10.1016/j.drudis.2011.09.013 · Cited by 22 · see citing works

Tracking 20 Years of Compound-to-Target Output from Literature and Patents

Southan, C., Varkonyi, P., Boppana, K., Jagarlapudi, S. A. R. P., & Mureşan, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0077142 · Cited by 22 · see citing works

Is Research Responding to Health Needs?Preprint

Ràfols, I., & Yegros, A. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3106713 · Cited by 22 · see citing works

Drug discovery in the next decade: innovation needed ASAP

Bennani, Y. L. (2011) · Drug Discovery Today · doi:10.1016/j.drudis.2011.12.007 · Cited by 21 · see citing works

Application of an automated natural language processing (NLP) workflow to enable federated search of external biomedical content in drug discovery and development

McEntire, R., Szalkowski, D., Butler, J., Kuo, M. S., Chang, M., Chang, M., Freeman, D., McQuay, S., Patel, J. H., McGlashen, M. L., et al. (2016) · Drug Discovery Today · doi:10.1016/j.drudis.2016.03.006 · Cited by 21 · see citing works

Global Research Trends and Future Directions in Urban Historical Heritage Area Conservation and Development: A 25-Year Bibliometric Analysis

Xia, J., Kang, J. X., & Xu, X. (2024) · Buildings · doi:10.3390/buildings14103096 · Cited by 19 · see citing works

Citation algorithms for identifying research milestones driving biomedical innovation

Comins, J. A., & Loet Leydesdorff, A. (2017) · Scientometrics · doi:10.1007/s11192-016-2238-1 · Cited by 19 · see citing works

Modeling timelines for translational science in cancer; the impact of technological maturation

McNamee, L. M., & Ledley, F. D. (2017) · PLoS ONE · doi:10.1371/journal.pone.0174538 · Cited by 19 · see citing works

Uncovering novel repositioning opportunities using the Open Targets platform

Khaladkar, M., Koscielny, G., Hasan, S., Agarwal, P., Dunham, I., Rajpal, D. K., & Sanséau, P. (2017) · Drug Discovery Today · doi:10.1016/j.drudis.2017.09.007 · Cited by 18 · see citing works

Retrofitting Concept Vector Representations of Medical Concepts to Improve Estimates of Semantic Similarity and Relatedness

Yu, Z., Wallace, B., Johnson, T. R., & Cohen, T. (2017) · PubMed · doi:10.48550/arxiv.1709.07357 · Cited by 18 · see citing works

The impact of external innovation on new drug approvals: A retrospective analysis

Liu, X., Thomas, C. E., & Felder, C. C. (2019) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2018.12.093 · Cited by 17 · see citing works

Global Research Status of Multiple Organ Dysfunction Syndrome During 2001–2021: A 20-Year Bibliometric Analysis

Zhao, P., Xia, Y. Q., Tao, Z., Li, S.-Y., Mao, Z., Yang, X., Yao, R.-Q., & Du, X. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.814381 · Cited by 16 · see citing works

The Cinderella of Biological Data Integration: Addressing Some of the Challenges of Entity and Relationship Mining from Patent Sources

Suriyawongkul, I., Southan, C., & Mureşan, S. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15120-0_9 · Cited by 15 · see citing works

An early indicator of drug success: Top Journal Selectivity Index

Kissin, I. (2013) · Drug Design Development and Therapy · doi:10.2147/dddt.s37324 · Cited by 15 · see citing works

Finding potentially new multimorbidity patterns of psychiatric and somatic diseases: exploring the use of literature-based discovery in primary care research

Vos, R., Aarts, S., van Mulligen, E. M., Metsemakers, J. F. M., van Boxtel, M. P. J., Verhey, F. R. J., & van den Akker, M. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001448 · Cited by 14 · see citing works

Statistics for the dynamic analysis of scientometric data: the evolution of the sciences in terms of trajectories and regimes

Loet Leydesdorff, A. (2012) · Scientometrics · doi:10.1007/s11192-012-0917-0 · Cited by 14 · see citing works

In silico Analysis of Molecular Mechanisms of Galanthus nivalis Agglutinin-Related Lectin-Induced Cancer Cell Death from Carbohydrate-Binding Motif Evolution Hypothesis

Yu, Q., Li, Z., Yao, S., Ming, M., Wang, S., Liu, B., & Bao, J. (2011) · Applied Biochemistry and Biotechnology · doi:10.1007/s12010-011-9318-8 · Cited by 14 · see citing works

Research Portfolios in Science Policy: Moving from Financial Returns to Societal BenefitsPreprint

Wallace, M. L., & Ràfols, I. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2743220 · Cited by 14 · see citing works

What Can Big Data on Academic Interest Reveal about a Drug? Reflections in Three Major US Databases

Kissin, I. (2018) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2017.12.005 · Cited by 13 · see citing works

Bibliometric Analysis of Chinese Research on Cyclization, MALDI-TOF, and Antibiotics

Li, J., & Willett, P. (2009) · Journal of Chemical Information and Modeling · doi:10.1021/ci9003199 · Cited by 13 · see citing works

Medical Innovation Then and Now: Perspectives of Innovators Responsible for Transformative Drugs

Xu, S., & Kesselheim, A. S. (2014) · The Journal of Law Medicine & Ethics · doi:10.1111/jlme.12176 · Cited by 12 · see citing works

Do national funding organizations properly address the diseases with the highest burden?: Observations from China and the UK

Zhang, L., Zhao, W., Liu, J., Sivertsen, G., & Huang, Y. (2020) · Scientometrics · doi:10.1007/s11192-020-03572-9 · Cited by 12 · see citing works

Mining Emerging Biomedical Literature for Understanding Disease Associations in Drug Discovery

Rajpal, D. K., Qu, X. A., Freudenberg, J., & Kumar, V. D. (2014) · Methods in molecular biology · doi:10.1007/978-1-4939-0709-0_11 · Cited by 11 · see citing works

Polydatin Ameliorates Osteoporosis via Suppression of the Mitogen-Activated Protein Kinase Signaling Pathway

Lin, Z., Xiong, Y., Hu, Y., Chen, L., Panayi, A. C., Xue, H., Zhou, W., Yan, C., Hu, L., Xie, X., et al. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.730362 · Cited by 11 · see citing works

Adoption of the Citation Typing Ontology by the Journal of Cheminformatics

Willighagen, E. (2020) · Journal of Cheminformatics · doi:10.1186/s13321-020-00448-1 · Cited by 11 · see citing works

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Gan, Z., Zhou, D., Rush, E. N., Panickan, V. A., Ho, Y.-L. A., Ostrouchovm, G., Xu, Z., Shen, S., Xiong, X., Greco, K. F., et al. (2025) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2024.104761 · Cited by 10 · see citing works

New Strategies and Paradigm for Drug Target Discovery: A Special Focus on Infectious Diseases Tuberculosis, Malaria, Leishmaniasis, Trypanosomiasis and Gastritis

Neelapu, N. R. R., Srimath-Tirumala-Peddinti, R. C. P. K., Nammi, D., & Pasupuleti, A. M. C. (2014) · Infectious Disorders - Drug Targets · doi:10.2174/1871526514666140321110312 · Cited by 10 · see citing works

Top journals selectivity index and “me-too” drugs

Kissin, I., & Bradley, E. L. (2011) · Scientometrics · doi:10.1007/s11192-011-0556-x · Cited by 10 · see citing works

Using ontology-based annotation to profile disease research

Liu, Y., Coulet, A., LePendu, P., & Shah, N. H. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000631 · Cited by 9 · see citing works

Exploiting Latent Semantic Subspaces to Derive Associations for Specific Pharmaceutical Semantics

Wawrzinek, J., Pinto, J. M. G., Wiehr, O., & Balke, W. (2020) · Data Science and Engineering · doi:10.1007/s41019-020-00140-2 · Cited by 9 · see citing works

Patent citation spectroscopy (PCS): Online retrieval of landmark patents based on an algorithmic approach

Comins, J. A., Carmack, S. A., & Loet Leydesdorff, A. (2018) · Journal of Informetrics · doi:10.1016/j.joi.2018.10.002 · Cited by 9 · see citing works

Exploring Why Global Health Needs Are Unmet by Research Efforts: The Potential Influences of Geography, Industry, and Publication IncentivesPreprint

Yegros, A., van de Klippe, W., García, M. F. A., & Ràfols, I. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3459230 · Cited by 9 · see citing works

Biomechanisms of Comorbidity: Reviewing Integrative Analyses of Multi-omics Datasets and Electronic Health Records

Pouladi, N., Achour, L., Li, H., Berghout, J., Kenost, C., Gonzalez‐Garay, M. L., & Lussier, Y. A. (2016) · Yearbook of Medical Informatics · doi:10.15265/iy-2016-040 · Cited by 8 · see citing works

Searching for new cardiovascular drugs: towards improved systems for drug screening?

Silvester, N. C., & George, C. H. (2011) · Expert Opinion on Drug Discovery · doi:10.1517/17460441.2011.625652 · Cited by 7 · see citing works

Scientific literature mining for drug discovery: a case study on obesity

Rajpal, D. K., Kumar, V. D., & Agarwal, P. (2010) · Drug Development Research · doi:10.1002/ddr.20416 · Cited by 7 · see citing works

The MeSH-gram Neural Network Model: Extending Word Embedding Vectors with MeSH Concepts for UMLS Semantic Similarity and Relatedness in the Biomedical DomainPreprint

Abdeddaïm, S., Vimard, S., & Soualmia, L. F. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1812.02309 · Cited by 7 · see citing works

Temporal trends in evidence supporting novel drug target discovery

Falaguera, M. J., McDonagh, E. M., Ochoa, D., Rusina, P. V., Roldán‐Romero, J. M., Hulcoop, D. G., Leach, A. R., & Dunham, I. (2025) · Nature Communications · doi:10.1038/s41467-025-67180-y · Cited by 6 · see citing works

US FDA Drug Approvals are Persistent and Polycyclic: Insights into Economic Cycles, Innovation Dynamics, and National Policy

Daizadeh, I. (2021) · Therapeutic Innovation & Regulatory Science · doi:10.1007/s43441-021-00279-8 · Cited by 6 · see citing works

Explainable Word-Embeddings for Medical Digital Libraries - A Context-Aware Approach

Wawrzinek, J., Hussaini, S. A. R., Wiehr, O., Pinto, J. M. G., & Balke, W. (2020) · ACM/IEEE Joint Conference on Digital Libraries · doi:10.1145/3383583.3398522 · Cited by 5 · see citing works

TeamTree analysis: A new approach to evaluate scientific production

Pfrieger, F. W. (2021) · PLoS ONE · doi:10.1371/journal.pone.0253847 · Cited by 5 · see citing works

Semantic Disambiguation of Embedded Drug-Disease Associations Using Semantically Enriched Deep-Learning Approaches

Wawrzinek, J., Pinto, J. M. G., Wiehr, O., & Balke, W. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59419-0_30 · Cited by 4 · see citing works

Measuring the Interactions Between Health Demand, Informatics Supply, and Technological Applications in Digital Medical Innovation for China: Content Mapping and Analysis

Du, J., Chen, T., & Zhang, L. (2021) · JMIR Medical Informatics · doi:10.2196/26393 · Cited by 4 · see citing works

Measuring the Semantic World – How to Map Meaning to High-Dimensional Entity Clusters in PubMed?

Wawrzinek, J., & Balke, W. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-04257-8_2 · Cited by 4 · see citing works

Research Portfolios in Science Policy: Moving from Financial Returns to Societal BenefitsPreprint

Wallace, M. L., & Ràfols, I. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2500396 · Cited by 4 · see citing works

Research on Electro-enhanced wastewater biological treatment from 2000 to 2023: A review and bibliometric analysis

Li, Y., Chung, J.-P., & Shi, H. (2025) · Chemical Engineering and Processing - Process Intensification · doi:10.1016/j.cep.2025.110182 · Cited by 3 · see citing works

Tackling the “So What” Problem in Scientific Research

Harris, P. A., Kirby, J., Swafford, J. A., Edwards, T. L., Zhang, M., Yarbrough, T. R., Lane, L. D., Helmer, T. T., Bernard, G. R., & Pulley, J. M. (2015) · Academic Medicine · doi:10.1097/acm.0000000000000732 · Cited by 3 · see citing works

DETECTION OF MYCOPLASMA SALIVARIUM CONTAMINATION IN CELL CULTURE USING PCR METHOD (SHORT COMMUNICATION)

Rostamizadeh, V., Pourbakhsh, S. A., Asli, E., & Hadadi, A. (2013) · Pathobiology Research · Cited by 3 · see citing works

A blueprint for an ideal corporate information centre

Renn, O., Archer, M., Burkhardt, C., Ginestet, J., Nielsen, H. P., & Woodward, J. (2012) · Nature Reviews Drug Discovery · doi:10.1038/nrd2973-c1 · Cited by 2 · see citing works

The global research status and trends of the application of endoscopic ultrasonography in pancreatic tumors over the last decades: A bibliometric study

Xia, C., Yin, H., Zhang, K., Wang, Z., Yang, X., & Huang, H. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.980415 · Cited by 2 · see citing works

Modeling the pulling and pushing power in medical research: Unmet health needs and unsettled scientific questions

Du, J., Zhao, W., Guo, X., & Dong, E. (2023) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2022-1310 · Cited by 2 · see citing works

The Interaction of 'Supply', 'Demand', and 'Technological Capabilities' in terms of Medical Subject Headings: A Triple Helix Model of Medical Innovation.Preprint

Petersen, A. M., Rotolo, D., & Loet Leydesdorff, A. (2015) · arXiv (Cornell University) · Cited by 2 · see citing works

Additional knowledge-based analysis approaches

Rodriguez‐Esteban, R. (2016) · Cambridge University Press eBooks · doi:10.1017/cbo9780511989421.011 · Cited by 1 · see citing works

A Triple Helix Model of Medical Innovation: Supply, Demand, and Technological Capabilities in Terms of Medical Subject HeadingsPreprint

Petersen, A. M., Rotolo, D., & Loet Leydesdorff, A. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2604702 · Cited by 1 · see citing works

The Identification of Target Proteins from Patents - Mining of biological entities from a full-text patent database

Suriyawongkul, I. (2010) · Chalmers Publication Library (Chalmers University of Technology)

Improved Health Monitoring Informatics by New Similarity Measures

Kakulapati, V., Balaram, V. V. S. S. S., & Krishna, P. (2017) · Advances in healthcare information systems and administration book series · doi:10.4018/978-1-5225-5222-2.ch012

La bibliométrie et l’innovation : l’étude de l’impact de la propriété intellectuelle sur le progrès scientifique

Hétu, M. (2018) · Ethics Medicine and Public Health · doi:10.1016/j.jemep.2018.01.001

TeamTree analysis: a new approach to evaluate scientific productionPreprint

Pfrieger, F. W. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.01.128355

Mining Emerging Biomedical Literature for Understanding Disease Associations in Drug Discovery

Rajpal, D. K., Qu, X. A., Freudenberg, J., & Kumar, V. D. (2014) · Methods in molecular biology · doi:10.1007/978-1-4939-0709-0_11 · Cited by 11 · see citing works

TrendyGenes, a computational pipeline for the detection of literature trends in academia and drug discovery

Nájera, G. S., Narganes-Carlón, D., & Crowther, D. J. (2021) · Scientific Reports · doi:10.1038/s41598-021-94897-9 · Cited by 9 · see citing works

Moving targets in drug discovery

Zdrazil, B., Richter, L., Brown, N., & Guha, R. (2020) · Scientific Reports · doi:10.1038/s41598-020-77033-x · Cited by 36 · see citing works

Automating Literature-Based Lead Discovery

Wren, J. D. (2010) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/978160805199110501010267

Forecasting novel therapeutic development in biomedical research

Arabi, S., & Hutchins, B. I. (2026) · Communications Medicine · doi:10.1038/s43856-026-01838-6 · Cited by 4 · see citing works