Literature DB >> 23995394

Quantifying the complexity of medical research.

Raul Rodriguez-Esteban1, William T Loging.   

Abstract

MOTIVATION: A crucial phenomenon of our times is the diminishing marginal returns of investments in pharmaceutical research and development. A potential reason is that research into diseases is becoming increasingly complex, and thus more burdensome, for humans to handle. We sought to investigate whether we could measure research complexity by analyzing the published literature.
RESULTS: Through the text mining of the publication record of multiple diseases, we have found that the complexity and novelty of disease research has been increasing over the years. Surprisingly, we have also found that research on diseases with higher publication rate does not possess greater complexity or novelty than that on less-studied diseases. We have also shown that the research produced about a disease can be seen as a differentiated area of knowledge within the wider biomedical research. For our analysis, we have conceptualized disease research as a parallel multi-agent search in which each scientific agent (a scientist) follows a search path based on a model of a disease. We have looked at trends in facts published for diseases, measured their diversity and turnover using the entropy measure and found similar patterns across disease areas. CONTACT: raul.rodriguez-esteban@roche.com.

Entities:  

Mesh:

Year:  2013        PMID: 23995394     DOI: 10.1093/bioinformatics/btt505

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  7 in total

1.  A new approach and gold standard toward author disambiguation in MEDLINE.

Authors:  Dina Vishnyakova; Raul Rodriguez-Esteban; Fabio Rinaldi
Journal:  J Am Med Inform Assoc       Date:  2019-10-01       Impact factor: 4.497

2.  Opinion: Is science really facing a reproducibility crisis, and do we need it to?

Authors:  Daniele Fanelli
Journal:  Proc Natl Acad Sci U S A       Date:  2018-03-13       Impact factor: 11.205

3.  NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease.

Authors:  Anandhi Iyappan; Shweta Bagewadi Kawalia; Tamara Raschka; Martin Hofmann-Apitius; Philipp Senger
Journal:  J Biomed Semantics       Date:  2016-07-08

4.  A Text Structuring Method for Chinese Medical Text Based on Temporal Information.

Authors:  Runtong Zhang; Fuzhi Chu; Donghua Chen; Xiaopu Shang
Journal:  Int J Environ Res Public Health       Date:  2018-02-27       Impact factor: 3.390

5.  The speed of information propagation in the scientific network distorts biomedical research.

Authors:  Raul Rodriguez-Esteban
Journal:  PeerJ       Date:  2022-01-10       Impact factor: 2.984

6.  A Drug-Centric View of Drug Development: How Drugs Spread from Disease to Disease.

Authors:  Raul Rodriguez-Esteban
Journal:  PLoS Comput Biol       Date:  2016-04-28       Impact factor: 4.475

7.  Differential gene expression in disease: a comparison between high-throughput studies and the literature.

Authors:  Raul Rodriguez-Esteban; Xiaoyu Jiang
Journal:  BMC Med Genomics       Date:  2017-10-11       Impact factor: 3.063

  7 in total

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