Prashanti Manda

514 total citations
31 papers, 276 citations indexed

About

Prashanti Manda is a scholar working on Molecular Biology, Artificial Intelligence and Geriatrics and Gerontology. According to data from OpenAlex, Prashanti Manda has authored 31 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 12 papers in Artificial Intelligence and 7 papers in Geriatrics and Gerontology. Recurrent topics in Prashanti Manda's work include Biomedical Text Mining and Ontologies (14 papers), Bioinformatics and Genomic Networks (11 papers) and Semantic Web and Ontologies (9 papers). Prashanti Manda is often cited by papers focused on Biomedical Text Mining and Ontologies (14 papers), Bioinformatics and Genomic Networks (11 papers) and Semantic Web and Ontologies (9 papers). Prashanti Manda collaborates with scholars based in United States and United Kingdom. Prashanti Manda's co-authors include Susan M. Bridges, Fiona McCarthy, Somya D. Mohanty, Thomas P. McCoy, Seval Ozkan, Deborah Lekan, Marjorie Jenkins, Shane C. Burgess, Todd Vision and James P. Balhoff and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Scientific Reports.

In The Last Decade

Prashanti Manda

29 papers receiving 273 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Prashanti Manda United States	9	145	79	46	25	20	31	276
Alexandros Kanterakis Greece	9	152 1.0×	66 0.8×	27 0.6×	13 0.5×	18 0.9×	32	371
Olufemi Aromolaran Nigeria	7	169 1.2×	66 0.8×	23 0.5×	16 0.6×	33 1.6×	14	328
George Potamias Greece	12	119 0.8×	92 1.2×	36 0.8×	4 0.2×	33 1.6×	52	356
Daniel Merl United States	6	98 0.7×	31 0.4×	37 0.8×	6 0.2×	2 0.1×	14	335
Ludger Jansen Germany	11	198 1.4×	155 2.0×	34 0.7×	1 0.0×	10 0.5×	58	355
Andrea Splendiani United Kingdom	10	234 1.6×	113 1.4×	62 1.3×	4 0.2×	25 1.3×	23	378
Leslie Derr United States	7	330 2.3×	39 0.5×	27 0.6×	62 2.5×	8 0.4×	7	468
Yaning Yang China	9	186 1.3×	44 0.6×	8 0.2×	9 0.4×	51 2.5×	19	317
José Augusto Baranauskas Brazil	8	112 0.8×	67 0.8×	27 0.6×	29 1.2×	10 0.5×	28	305

Countries citing papers authored by Prashanti Manda

Since Specialization

Citations

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

Fields of papers citing papers by Prashanti Manda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Prashanti Manda

This figure shows the co-authorship network connecting the top 25 collaborators of Prashanti Manda. A scholar is included among the top collaborators of Prashanti Manda 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 Prashanti Manda. Prashanti Manda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Manda, Prashanti. (2025). Large Language Models in Bio-Ontology Research: A Review. Bioengineering. 12(11). 1260–1260.

Mohanty, Somya D., et al.. (2025). Leveraging Large Language Models and RNNs for Accurate Ontology-Based Text Annotation. 489–494. 1 indexed citations

Mohanty, Somya D., et al.. (2023). A deep semantic matching approach for identifying relevant messages for social media analysis. Scientific Reports. 13(1). 12005–12005. 7 indexed citations

Mohanty, Somya D., et al.. (2023). Ontology-Powered Boosting for Improved Recognition of Ontology Concepts from Biological Literature. 80–90. 1 indexed citations

Mohanty, Somya D., et al.. (2022). A Gated Recurrent Unit based architecture for recognizing ontology concepts from biological literature. BioData Mining. 15(1). 22–22. 1 indexed citations

Lekan, Deborah, Thomas P. McCoy, Marjorie Jenkins, Somya D. Mohanty, & Prashanti Manda. (2021). Frailty and In-Hospital Mortality Risk Using EHR Nursing Data. Biological Research For Nursing. 24(2). 186–201. 1 indexed citations

Mohanty, Somya D., Deborah Lekan, Thomas P. McCoy, Marjorie Jenkins, & Prashanti Manda. (2021). Machine learning for predicting readmission risk among the frail: Explainable AI for healthcare. Patterns. 3(1). 100395–100395. 35 indexed citations

Mohanty, Somya D., Deborah Lekan, Thomas P. McCoy, Marjorie Jenkins, & Prashanti Manda. (2021). Machine Learning for Predicting Readmission Risk Among the Frail - Explainable AI for Healthcare. SSRN Electronic Journal. 1 indexed citations

Manda, Prashanti, et al.. (2020). Automated ontology-based annotation of scientific literature using deep learning. 1–6. 6 indexed citations

10.

Amiri, Esmaeil, et al.. (2020). Using Manual and Computer-Based Text-Mining to Uncover Research Trends for Apis mellifera. Veterinary Sciences. 7(2). 61–61. 3 indexed citations

11.

Mohanty, Somya D., Deborah Lekan, Thomas P. McCoy, Marjorie Jenkins, & Prashanti Manda. (2020). A multi-modal machine learning approach towards predicting patient readmission. 2027–2035. 2 indexed citations

12.

Manda, Prashanti, et al.. (2018). Taking a Dive: Experiments in Deep Learning for Automatic Ontology-Based Annotation of Scientific Literature.. 1 indexed citations

13.

Manda, Prashanti. (2018). On the Statistical Sensitivity of Semantic Similarity Metrics.. 2 indexed citations

14.

Manda, Prashanti, et al.. (2018). Comparison of natural language processing tools for automatic gene ontology annotation of scientific literature. 2 indexed citations

15.

Manda, Prashanti, James P. Balhoff, Hilmar Lapp, Paula Mabee, & Todd Vision. (2015). Using the phenoscape knowledgebase to relate genetic perturbations to phenotypic evolution. genesis. 53(8). 561–571. 9 indexed citations

16.

Manda, Prashanti, Fiona McCarthy, & Susan M. Bridges. (2013). Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships. Journal of Biomedical Informatics. 46(5). 849–856. 20 indexed citations

17.

Manda, Prashanti, Seval Ozkan, Hui Wang, Fiona McCarthy, & Susan M. Bridges. (2012). Cross-Ontology Multi-level Association Rule Mining in the Gene Ontology. PLoS ONE. 7(10). e47411–e47411. 26 indexed citations

18.

McCarthy, Fiona, Cathy Gresham, Philippe Chouvarine, et al.. (2010). AgBase: supporting functional modeling in agricultural organisms. Nucleic Acids Research. 39(suppl_1). D497–D506. 49 indexed citations

19.

Manda, Prashanti, Susan M. Bridges, T. J. Jankun-Kelly, et al.. (2010). GOModeler- A tool for hypothesis-testing of functional genomics datasets. BMC Bioinformatics. 11(S6). S29–S29. 10 indexed citations

20.

Manda, Prashanti, et al.. (2009). Comparing gene annotation enrichment tools for functional modeling of agricultural microarray data. BMC Bioinformatics. 10(S11). S9–S9. 24 indexed citations

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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