scholarly journals Objective, Quantitative, Data-Driven Assessment of Chemical Probes

2017 ◽  
Author(s):  
Albert A. Antolin ◽  
Joe E. Tym ◽  
Angeliki Komianou ◽  
Ian Collins ◽  
Paul Workman ◽  
...  
Keyword(s):  
Big Data ◽  
Biomedical Research ◽  
Quantitative Data ◽  
Medicinal Chemistry ◽  
Objective Assessment ◽  
Data Driven ◽  
Target Validation ◽  
Chemical Probes ◽  
Chemistry Data ◽  
Assessment Resource

ABSTRACTChemical probes are essential tools for understanding biological systems and for target validation, yet selecting tools for biomedical research is largely biased and subjective. Here we describe the Probe Miner: Chemical Probes Objective Assessment resource – capitalising on the plethora of public medicinal chemistry data to empower quantitative, objective, Big Data-driven assessment of chemical probes. We assess >1.8m compounds for their suitability as chemical tools against 2,220 human targets and dissect their biases and limitations.

Abstract A024: Probe Miner: objective, quantitative, data-driven assessment of chemical probes for target validation

2018 ◽  
Author(s):  
Albert A. Antolin ◽  
Joe E. Tym ◽  
Angeliki Komianou ◽  
Ian Collins ◽  
Paul Workman ◽  
...  
Keyword(s):  
Quantitative Data ◽  
Data Driven ◽  
Target Validation ◽  
Chemical Probes

Data-driven medicinal chemistry in the era of big data

2014 ◽  
Vol 19 (7) ◽  
pp. 859-868 ◽  
Author(s):  
Scott J. Lusher ◽  
Ross McGuire ◽  
René C. van Schaik ◽  
C. David Nicholson ◽  
Jacob de Vlieg
Keyword(s):  
Big Data ◽  
Medicinal Chemistry ◽  
Data Driven

scholarly journals Big Data for Biomedical Research and Personalised Medicine: an Epistemological and Ethical Cross-Analysis

2017 ◽  
Vol 6 (3) ◽  
pp. 13-36
Author(s):  
Mathieu Guillermin ◽  
Thierry Magnin
Keyword(s):  
Health Care ◽  
Big Data ◽  
Biomedical Research ◽  
Privacy Protection ◽  
Personalised Medicine ◽  
Data Driven ◽  
Human Intelligence

Abstract Big data techniques, data-driven science and their technological applications raise many serious ethical questions, notably about privacy protection. In this paper, we highlight an entanglement between epistemology and ethics of big data. Discussing the mobilisation of big data in the fields of biomedical research and health care, we show how an overestimation of big data epistemic power – of their objectivity or rationality understood through the lens of neutrality – can become ethically threatening. Highlighting the irreducible non-neutrality at play in big data tools, we insist upon the ethical importance of a critical epistemological approach in which big data are understood as possibly valuable only when coupled with human intelligence and evaluative rationality.

scholarly journals Objective, Quantitative, Data-Driven Assessment of Chemical Probes

2018 ◽  
Vol 25 (2) ◽  
pp. 194-205.e5 ◽  
Author(s):  
Albert A. Antolin ◽  
Joseph E. Tym ◽  
Angeliki Komianou ◽  
Ian Collins ◽  
Paul Workman ◽  
...  
Keyword(s):  
Quantitative Data ◽  
Data Driven ◽  
Chemical Probes

scholarly journals Finding the right approach to big data-driven medicinal chemistry

2015 ◽  
Vol 7 (10) ◽  
pp. 1213-1216 ◽  
Author(s):  
Scott J Lusher ◽  
Tina Ritschel
Keyword(s):  
Big Data ◽  
Medicinal Chemistry ◽  
Data Driven ◽  
The Right

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

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