Chandra Das

888 citations
54 papers · 699 · h-index 15

Impact in

    • Histone Deacetylase Inhibitors Research
    • Epigenetics and DNA Methylation
    • Gene expression and cancer classification
    • Ubiquitin and proteasome pathways
    • Glioma Diagnosis and Treatment

Papers in

    • Gene expression and cancer classification 16
    • Bioinformatics and Genomic Networks 6
    • Machine Learning in Bioinformatics 5
    • Histone Deacetylase Inhibitors Research 4

Chandra Das

53 papers receiving 651 citations

Peers

Chandra Das
Comparison fields: 5 of 124
  • Molecular Biology 315
  • Genetics 45
  • Immunology 82
  • Obstetrics and Gynecology 22
  • Cancer Research 35
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Citations per field
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Citations per year

Countries citing papers authored by Chandra Das

Since Specialization
Citations

This map shows the geographic impact of Chandra Das'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 Chandra Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chandra Das more than expected).

Fields of papers citing papers by Chandra Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chandra Das. 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 Chandra Das. The network helps show where Chandra Das may publish in the future.

Co-authors

The 25 scholars most cited alongside Chandra Das, 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 Chandra Das Line = papers co-authored together Chandra Das links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200795
2 200574
3 201238
4 200938
5 198737
6 198435
7
Measuring cytotoxicity: a new perspective on LC50.
200734
8 201728
9 201227
10 201124
11 200819
12 198319
13 201016
14
Genito-urinary fistula: a major morbidity in developing countries.
201116
15 199314
16 198914
17
Predicting tumor cell repopulation after response: mathematical modeling of cancer cell growth.
200613
18 202012
19 198511
20 198511

About Chandra Das

Chandra Das is a scholar working on Molecular Biology, Genetics, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Information Systems, having authored 54 papers that have together received 699 indexed citations. Recurring topics across this work include Gene expression and cancer classification (16 papers), Face and Expression Recognition (6 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Bioinformatics and Genomic Networks (6 papers), Machine Learning in Bioinformatics (5 papers), Data Mining Algorithms and Applications (4 papers), Histone Deacetylase Inhibitors Research (4 papers) and Herpesvirus Infections and Treatments (3 papers). The work is most often cited by research in Molecular Biology (315 citations), Genetics (45 citations), Immunology (82 citations), Obstetrics and Gynecology (22 citations) and Cancer Research (35 citations). Chandra Das has collaborated with scholars based in India, United States and Pakistan. Frequent co-authors include Vidya Gopalakrishnan, John J. Langone, Johannes Wolff, Dolly Aguilera, Hernán Vásquez, K. J. Catt, Pradipta Maji, Frederick F. Becker, Jamileh Noshari and Peter R. C. Gascoyne. Their work appears in journals such as IEEE Transactions on NanoBioscience, Journal of Neuro-Oncology, Molecular and Cellular Biochemistry, The Journal of Immunology and Analytical Biochemistry.

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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