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Introduction Text mining and knowledge discovery from biomedical literature play important roles in drug discovery, clinical therapy, pathology research, etc. Typical tasks include recognizing named entities in the articles, mining the interaction between drugs and proteins/diseases/other drugs, answering questions given reference text, generating abstracts for given phrases/words, etc. People hav
Survival of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Influenza Virus on Human Skin: Importance of Hand Hygiene in Coronavirus Disease 2019 (COVID-19)
Mass Screening of Asymptomatic Persons for Severe Acute Respiratory Syndrome Coronavirus 2 Using Saliva
Virucidal Efficacy of Different Oral Rinses Against Severe Acute Respiratory Syndrome Coronavirus 2
Surgical Mask Partition Reduces the Risk of Noncontact Transmission in a Golden Syrian Hamster Model for Coronavirus Disease 2019 (COVID-19)
The evidence is admittedly incomplete for all the steps in COVID-19 microdroplet transmission, but it is similarly incomplete for the large droplet and fomite modes of transmission. The airborne transmission mechanism operates in parallel with the large droplet and fomite routes [16] that are now the basis of guidance. Following the precautionary principle, we must address every potentially import
State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University
COVID-19 outbreak on the Diamond Princess cruise ship: estimating the epidemic potential and effectiveness of public health countermeasures
General inference problems and quantifying uncertainty have long been the cornerstone of statistical science. While machine learning advances have permeated many disciplines, inference for these procedures, and in particular, causal inference, has not been widespread. However, this is rapidly changing. As different scientific fields begin to converge on machine learning for causal inference, we th
Reflection on modern methods: when worlds collide—prediction, machine learning and causal inference
Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT Correspondence to: Skyler B. Johnson, MD, Department of Therapeutic Radiology, Yale School of Medicine, HRT 138, 333 Cedar St, New Haven, CT 06520 (e-mail: skyler.johnson@yale.edu).
1National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan 2Department of Informatics, SOKENDAI (Graduate University for Advanced Studies), 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
Nucleic Acids Research, Volume 42, Issue D1, 1 January 2014, Page i, https://doi.org/10.1093/nar/gks1388
Briefings in Bioinformatics, Volume 14, Issue 5, September 2013, Page 527, https://doi.org/10.1093/bib/bbt064
“Data is not information, information is not knowledge, knowledge is not wisdom, wisdom is not truth,” —Robert Royar (1994) paraphrasing Frank Zappa’s (1979) anadiplosis “I would be quite proud to have served on the committee that designed the E. coli genome. There is, however, no way that I would admit to serving on a committee that designed the human genome. Not even a university committee could
Our partner presses within University Press Scholarship Online have now migrated to Oxford Academic. Read more about books migrating to Oxford Academic. If you are looking for a specific book simply type the book’s title or ISBN into the search bar at the top right of the screen. You may need to then refine or modify your search to find exactly what you’re looking for. You can also search across a
INTRODUCTION Recent advances in life sciences technology have dramatically changed the research style from hypothesis-driven research (bottom-up style) to data-driven research (top-down style). Current ‘omics’ projects have produced vast amounts of data that have been stored in various online databases. Simultaneously, many types of web tools have been developed to analyze the stored data. Some of
Carcinogenesis vol.30 no.11 pp.1821–1831, 2009 doi:10.1093/carcin/bgp193 Advance Access publication July 30, 2009 REVIEW Urinary bladder carcinogenesis induced by chronic exposure to persistent low-dose ionizing radiation after Chernobyl accident Alina Romanenko, Anna Kakehashi1 , Keiichirou Morimura1 , Hideki Wanibuchi1,� , Min Wei1 , Alexander Vozianov2 and Shoji Fukushima1,3 Department of Patho
Urinary bladder carcinogenesis induced by chronic exposure to persistent low-dose ionizing radiation after Chernobyl accident
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