Binata Halder

1.2k citations
8 papers · 767 · 1 hit paper · h-index 6

Impact in

Papers in

    • RNA and protein synthesis mechanisms 5
    • RNA modifications and cancer 4
    • Genomics and Phylogenetic Studies 3
    • Machine Learning in Bioinformatics 1
    • ATP Synthase and ATPases Research 1

Binata Halder

8 papers receiving 756 citations

Binata Halder's Hit Papers

A review on coronary artery disease, its risk factors, and therapeutics 2019 · 681 citations
6810+2+4Years since publication200400600

Peers

Binata Halder
Comparison fields: 5 of 115
  • Cardiology and Cardiovascular Medicine 273
  • Cancer Research 91
  • Health Information Management 26
  • Radiology, Nuclear Medicine and Imaging 107
  • Immunology 86
Replace Prosenjit Paul with:
Prosenjit Paul India
Mariateresa Pucci Italy
Rongrong Sun China
Richard Ferraro United States
Denis Kazakiewicz Belgium
Sui‐Lung Su Taiwan
Hong Ma China
Wei Hsian Yin Taiwan
Binata Halder relative to Prosenjit Paul India Prosenjit Paul's profile →
Citations per field
00.5×1.5×
Prosenjit Paul · 1×
Citations per year

Countries citing papers authored by Binata Halder

Since Specialization
Citations

This map shows the geographic impact of Binata Halder's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Binata Halder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Binata Halder more than expected).

Fields of papers citing papers by Binata Halder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Binata Halder. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Binata Halder. The network helps show where Binata Halder may publish in the future.

Co-authors

The 6 scholars most cited alongside Binata Halder, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Binata Halder Line = papers co-authored together Binata Halder links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1
A review on coronary artery disease, its risk factors, and therapeutics
Hit paper breakdown →
2019681
2 201633
3 201714
4 201612
5 201711
6 201910
7 20155
8 20171

About Binata Halder

Binata Halder is a scholar working on Molecular Biology, Otorhinolaryngology, Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging, having authored 8 papers that have together received 767 indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (5 papers), RNA modifications and cancer (4 papers), Genomics and Phylogenetic Studies (3 papers), Atherosclerosis and Cardiovascular Diseases (1 paper), Machine Learning in Bioinformatics (1 paper), Cystic Fibrosis Research Advances (1 paper), ATP Synthase and ATPases Research (1 paper) and NF-κB Signaling Pathways (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (273 citations), Cancer Research (91 citations), Health Information Management (26 citations), Radiology, Nuclear Medicine and Imaging (107 citations) and Immunology (86 citations). Binata Halder has collaborated with scholars based in India and United States. Frequent co-authors include Supriyo Chakraborty, Prosenjit Paul, Arif Uddin, Arup Kumar Malakar, Supriyo Chakraborty and Supriyo Chakraborty. Their work appears in journals such as Gene, Mitochondrion, Genomics, European Journal of Cancer Prevention and Journal of Cellular Physiology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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