Meghana Kshirsagar
- Molecular Biology
- Signal Processing top 10%
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 5%
- Developmental Biology top 5%
- Co-authors
- Judith Klein‐SeetharamanJuan Lavista FerresBhavana DalviS. SudarshanJaime CarbonellShahrzad GholamiGaurav GuptaMing Zhong
- Topics
- Machine Learning in Bioinformatics (9 papers)Protein Structure and Dynamics (8 papers)Bioinformatics and Genomic Networks (7 papers)
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Meghana Kshirsagar
24 papers receiving 585 citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Molecular Biology 315
- Signal Processing 98
- Artificial Intelligence 93
- Computational Theory and Mathematics 91
- Developmental Biology 55
Countries citing papers authored by Meghana Kshirsagar
This map shows the geographic impact of Meghana Kshirsagar'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 Meghana Kshirsagar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Meghana Kshirsagar more than expected).
Fields of papers citing papers by Meghana Kshirsagar
This network shows the impact of papers produced by Meghana Kshirsagar. 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 Meghana Kshirsagar. The network helps show where Meghana Kshirsagar may publish in the future.
Co-authorship network of co-authors of Meghana Kshirsagar
This figure shows the co-authorship network connecting the top 25 collaborators of Meghana Kshirsagar. A scholar is included among the top collaborators of Meghana Kshirsagar 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 Meghana Kshirsagar. Meghana Kshirsagar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 25 | |
| 4 | An epigenetic barrier sets the timing of human neuronal maturationbreakdown → | 77 |
| 5 | 8 | |
| 6 | 86 | |
| 7 | 13 | |
| 8 | 6 | |
| 9 | 8 | |
| 10 | 3 | |
| 11 | 6 | |
| 12 | 76 | |
| 13 | 24 | |
| 14 | 0 | |
| 15 | 3 | |
| 16 | 4 | |
| 17 | 20 | |
| 18 | 11 | |
| 19 | 64 | |
| 20 | 20 |
About Meghana Kshirsagar
Meghana Kshirsagar is a scholar working on Developmental Biology, Computational Theory and Mathematics and Developmental Neuroscience, having authored 25 papers that have together received 594 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (9 papers), Protein Structure and Dynamics (8 papers) and Bioinformatics and Genomic Networks (7 papers). The work is most often cited by research in Developmental Biology (55 citations), Signal Processing (98 citations) and Computational Theory and Mathematics (91 citations). Meghana Kshirsagar has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Judith Klein‐Seetharaman, Juan Lavista Ferres, Bhavana Dalvi, S. Sudarshan, Jaime Carbonell, Shahrzad Gholami, Gaurav Gupta, Ming Zhong, Gregory R. Bowman and Michael D. Ward. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.
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.