Quinacrine and Berberine as Antiviral Agents against Dengue and Zika Fever: In Silico Approach- Crimson Publishers

Quinacrine and Berberine as Antiviral Agents against Dengue and Zika Fever: In Silico Approach by Vivek Srivastava in OpenAccess Biostatistics & Bioinformatics: Crimson Publishers- Open Access Biostatistics & Bioinformatics journals

TDengue and Zika fever are mosquito-borne viral diseases that have rapidly spread in all over world. Currently there are no specific drugs for DENV and ZIKV infection. The recent outbreak of these viruses realized that there are major health risks, demands an enhanced surveillance and a need to develop novel drugs against them. Non-structural proteins NS5 and NS3 are essential for the replication of the flavi-viral RNA genome. Therefore its inhibition could be considered as a useful strategy for treatment of DENV and ZIKV infection. Quinacrine and Berberine had been docked with NS5-methyltransferase of Dengue virus and NS3 protein of ZIKV using Auto dock 4.2 tools. Quinacrine and Berberine showed binding affinity -6.83kcal/mol and -6.22kcal/mol with NS5-methyltransferase and -7.32kcal/mol and -8.03kcal/mol with NS3 protease of ZIKV, respectively. Observations discussion in review will be useful in designing single drug against both virus infections.

https://crimsonpublishers.com/oabb/fulltext/OABB.000532.php

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Untargeted UPLC-MS Downstream Data Processing and Statistical Analysis - Illustrated by a Pilot Study on Cognitive Impairment- Crimson Publishers

Untargeted UPLC-MS Downstream Data Processing and Statistical Analysis - Illustrated by a Pilot Study on Cognitive Impairment by TANG Xingyu in Open Access Biostatistics & Bioinformatics: Crimson Publishers- Open Access Biostatistics & Bioinformatics journals

This article is to introduce the procedure of untargeted ultra-performance liquid chromatography-mass spectrometry(UPLC-MS) downstream data processing and statistical analysis, developed and optimized in Singapore Phenome Centre (SPC). The procedure is illustrated by a pilot study on cognitive impairment.

https://crimsonpublishers.com/oabb/fulltext/OABB.000531.php

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The Privacy Dilemma for Official Statistics in a Big Data World- Crimson Publishers

The Privacy Dilemma for Official Statistics in a Big Data World by Steve Mac Feely in Open Access Biostatistics &Bioinformatic: Crimson Publishers- Bioinformatics Open Access Journals

Over recent years the potential of big data for government, for business, for society has excited much comment, debate and even evangelism. Described as the ‘new science’ with all the answers [1] or a paradigm destroying phenomena of enormous potential [2] big data are all the rage. Official statisticians, already with a long history of using non-survey data, which are often very large in terms of volume, must decide whether big data is really something new and useful or just hype. On the one hand, some argue that big data needs to be seen as an entirely new ecosystem comprising new data, new tools and methods [3]. Whereas others argue to the contrary that big data is just hype and that big data are just Data [4]. In deciding whether big data can be useful for official statistics, National Statistics Offices (NSOs) must keep the protection of confidential data at the top of their decision making tree.

https://crimsonpublishers.com/oabb/fulltext/OABB.000526.php

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Bioinformatics: An Introduction- Crimson Publishers

Bioinformatics: An Introduction by Nidhi Mishra in Open Access Biostatistics & Bioinformatic: Crimson Publishers- Open Access Biostatistics & Bioinformatics journals

An unprecedented revolution has been observed in science with recent technological advances, which have provided a large amount of “omic” data. The crescent generation and availability of this information available in public databases were, and still are, a challenge for professionals from different areas. However, what is the challenge? In biology, the main challenge is to make sense of the enormous amount of structural data and sequences that have been generated at multiple levels of biological systems. Still, in bioinformatics, development of tools is necessary (statistical and computational) capable of assisting in understanding the mechanisms underlying biological questions in the study. Besides, if we consider the complexity of science, this is a highly reductionist view. The era of a “new biology” emerges accompanied by the birth/development of other sciences, such as bioinformatics and computational biology, which have an integrated interface of molecular biology.

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Mining Online Author’s Publication to Report the Core Research Domain with PubMed MeSH Terms: a Systematic Review for a Journal- Crimson Publishers

Mining Online Author’s Publication to Report the Core Research Domain with PubMed MeSH 

Terms: a Systematic Review for a Journal by Tsair Wei Chien in Open Access Biostatistics & 

Bioinformatic: Crimson Publishers_ Bioinformatics Open Access Journals

Background: Identifying an author’s research domain (RD) using MeSH (Medical Subject Headings)
terms is essential for a journal’s development and its readership, but no journal uses mining online 
methods or social network analysis (SNA) to extract journal publication information to report an 
author’s contributions.


Objective: To select prestigious authors and papers that have contributed most to a journal, 
we retrospectively (1) calculated an SCI (Science Citation Index) journal’s most recent impact 
factors (IF) and (2) used graphical representations that include MeSH terms of RDs for authors 
and journals.


Methods: We collected 2,053 papers published between July 1, 1999, and April 3, 2017, in the 
Journal of Medical Internet Research (JMIR) and cited by 673 journals, for which we also 
collected annual IFs for 394 SCI journals, including the JMIR. The prestigious authors and JMIR 
papers based on the weight of the 5-year SCI IFs from 394 cited-by papers in 2015. The JMIR 
core aims and scope are presented using major MeSH terms based on their corresponding 
average weighted scores. Social network analysis was used to create a graphical RD pattern for 
JMIR, and its prestigious papers and authors.


Results: All JMIR 5-year IFs have not been less than 2.9 for the past 14 years. The authors who 
contributed most to JMIR in a number of publications and weighted citations are Gunther 
Eysenbach and My Hua. Their cohesion measures (ranging from 0 to 1.0) to JMIR are 34% and 
5.7%, respectively. The highest prestige weighted contribution among papers published in JMIR 
is the one (PMID: 23567935 /DOI: 10.2196/jmir.2324) with a cohesion measure of 4.5%.


Conclusion: An author’s research domain is required with an essential and graphical 
presentation along with the author’s submission to the target journal. Journal editors also 
look forward to evaluating an author’s research domain and the submitted paper’s cohesion 
measure for the journal.


https://crimsonpublishers.com/oabb/fulltext/OABB.000515.php

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