Sushil Kumar Shakyawar
- Molecular Biology top 10%
- Computational Theory and Mathematics top 0.5%
- Artificial Intelligence top 5%
- Health Information Management top 0.5%
- Materials Chemistry
- Co-authors
- Sandeep KaushikLokesh SharmaSabyasachi DashTero AittokallioAgnieszka SzwajdaJing TangKrister WennerbergAntti Airola
- Topics
- Bioinformatics and Genomic Networks (5 papers)Computational Drug Discovery Methods (3 papers)Gene expression and cancer classification (3 papers)
- Partner nations
- United StatesFinlandIndia
In The Last Decade
Sushil Kumar Shakyawar
14 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Molecular Biology 772
- Computational Theory and Mathematics 719
- Artificial Intelligence 262
- Health Information Management 232
- Materials Chemistry 228
Countries citing papers authored by Sushil Kumar Shakyawar
This map shows the geographic impact of Sushil Kumar Shakyawar'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 Sushil Kumar Shakyawar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sushil Kumar Shakyawar more than expected).
Fields of papers citing papers by Sushil Kumar Shakyawar
This network shows the impact of papers produced by Sushil Kumar Shakyawar. 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 Sushil Kumar Shakyawar. The network helps show where Sushil Kumar Shakyawar may publish in the future.
Co-authorship network of co-authors of Sushil Kumar Shakyawar
This figure shows the co-authorship network connecting the top 25 collaborators of Sushil Kumar Shakyawar. A scholar is included among the top collaborators of Sushil Kumar Shakyawar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sushil Kumar Shakyawar. Sushil Kumar Shakyawar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 7 | |
| 6 | 10 | |
| 7 | 21 | |
| 8 | 4 | |
| 9 | Big data in healthcare: management, analysis and future prospectsbreakdown → | 864 |
| 10 | 16 | |
| 11 | Making Sense of Large-Scale Kinase Inhibitor Bioactivity Data Sets: A Comparative and Integrative Analysisbreakdown → | 377 |
| 12 | Toward more realistic drug-target interaction predictionsbreakdown → | 379 |
| 13 | 1 | |
| 14 | Genome Analysis of Selected Foodborne Pathogens for Identification of Drug Targets | 1 |
| 15 | 8 | |
| 16 | 9 |
About Sushil Kumar Shakyawar
Sushil Kumar Shakyawar is a scholar working on Applied Microbiology and Biotechnology, Health Information Management and Molecular Medicine, having authored 16 papers that have together received 1.7k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Computational Drug Discovery Methods (3 papers) and Gene expression and cancer classification (3 papers). The work is most often cited by research in Health Informatics (116 citations), Health Information Management (232 citations) and Computational Theory and Mathematics (719 citations). Sushil Kumar Shakyawar has collaborated with scholars based in United States, Finland and India. Frequent co-authors include Sandeep Kaushik, Lokesh Sharma, Sabyasachi Dash, Tero Aittokallio, Agnieszka Szwajda, Jing Tang, Krister Wennerberg, Antti Airola, Samuli Pietilä and Tao Xu. Their work appears in journals such as Development, Cancer Research and Radiation Research.
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.