Rising Strengths Hong Kong SAR in Bioinformatics.

Chiranjib Chakraborty, C George Priya Doss, Hailong Zhu, Govindasamy Agoramoorthy

Abstract readReview

In one paragraph

Review in Interdisciplinary sciences, computational life sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

STS-NLSP: A Network-Based Label Space Partition Method for Predicting the Specificity of Membrane Transporter Substrates Using a Hybrid Feature of Structural and Semantic Similarity.Frontiers in bioengineering and biotechnology · 2019
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chiranjib ChakrabortyDepartment of Bio-informatics, School of Computer and Information Sciences, Galgotias University, Greater Noida, UP, 201306, India.

C George Priya DossMedical Biotechnology Division, School of BioSciences and Technology, VIT University, Vellore, TN, 632014, India.

Hailong ZhuDepartment of Computer Sciences, Hong Kong Baptist University, Kowloon Tong, Hong Kong. hlzhu@comp.hkbu.edu.hk.

Govindasamy AgoramoorthyCollege of Pharmacy and Health Care, Tajen University, Yanpu, Pingtung, 907, Taiwan. agoram@tajen.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hong Kong's bioinformatics sector is attaining new heights in combination with its economic boom and the predominance of the working-age group in its population. Factors such as a knowledge-based and free-market economy have contributed towards a prominent position on the world map of bioinformatics. In this review, we have considered the educational measures, landmark research activities and the achievements of bioinformatics companies and the role of the Hong Kong government in the establishment of bioinformatics as strength. However, several hurdles remain. New government policies will assist computational biologists to overcome these hurdles and further raise the profile of the field. There is a high expectation that bioinformatics in Hong Kong will be a promising area for the next generation.

Indexed as

Computational BiologyGovernment RegulationHong KongPublic PolicyBioinformatics educationBioinformatics researchGovernment roleHong Kong SAR

Identifiers

PMID26961385

DOI10.1007/s12539-016-0147-x

PMCPMC7091071

What OpenQuestion holds

Textmetadata

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.