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005        20230112102823.0
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245 00 |a Big Data Analysis on Adverse Effects of Aquatic Pharmaceutical Contaminants to Human Health |h [electronic resource].
260        |a Edison, NJ : |b Middlesex College, |c 2021.
490        |a Student Symposium 2022.
520 3    |a A recent publication by the USGS reported the presence of 88 pharmaceutical compounds in 308 streams across the USA. These findings point to a nation-wide environmental concern and pose a risk to human and aquatic-ecosystem’s health. Hence there is a need to generate a complete picture of disease risk, by constructing a conceptual map illustrating the link between the contaminating chemicals and diseases. This study is not simple, given the complex nature of disease mechanism and the mode of action of the chemicals analyzed. Today where analytical chemistry methods are useful in detecting the presence of pharmaceuticals in water, they are insufficient to understand the direct, harmful effects of pharmaceuticals getting into humans through the ecosystem of the water bodies. Herein, we have carried out “Big Data” analysis to identify the disease-association of these 88 compounds. We have extracted data from the Comparative Toxicogenomics Database, Drugbank and used the Cytoscape software to construct the chemical-disease networks to explore the breadth of the issue. Using Cytoscape to study biological networks, begins with building a combined network for the topic of interest and mapping the curated network for analysis. Being able to visualize combined and curated data allows the researcher to understand and evaluate targeted information. In our studies the (a) 88 chemicals were linked to about 2208 data points spanning several diseases; (b) diseases were distributed in 19 classes; (c) Disease/Chemical associations were generated for the most harmful chemicals and major diseases. Hence, the disease map generated by this study can be helpful in strategizing proper healthcare efforts in the event of a contamination crisis.
533        |a Electronic reproduction. |c Middlesex County College Institution, |d 2023. |f (Middlesex County College) |n Mode of access: World Wide Web. |n System requirements: Internet connectivity; Web browser software.
535 1    |a Middlesex County College Institution.
648        |a 2020-2021 |y Academic Year 2020-2021.
650    0 |a College students -- poster presentations.
650    0 |a Student Works -- Natural Sciences -- poster presentations.
650    0 |a Molecular Biology.
650    0 |a Biochemistry.
650        |a Middlesex College (Edison, NJ) -- Student works.
650    0 |a Middlesex County College (Edison, NJ).
650        |a big data analysis; .
650        |a chemical-disease networks.
650        |a pharmaceutical contaminants.
650        |a network biology.
650        |a Human Health.
650        |a environment.
720 1    |a Trivedi, Nirali, |e author, primary. |4 aut_prim
720 1    |a Ganesan, Vinayak, |e author, primary. |4 aut_prim
720 1    |a Ghosh, Phalguni. |4 ths
830    0 |a Middlesex County College.
830    0 |a Student Symposium.
830    0 |a Student Works.
852        |a MCC |c Student Symposium
856 40 |u http://middlesexcc.sobeklibrary.com/AA00002891/00001 |y Electronic Resource
992 04 |a https:/digital.middlesexcc.edu/content/AA/00/00/28/91/00001/Nirali and Vinyak Joint works SP-2021thm.jpg
997        |a Student Symposium


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