Prasenjit Mukherjee

1.1k total citations
47 papers, 751 citations indexed

About

Prasenjit Mukherjee is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Prasenjit Mukherjee has authored 47 papers receiving a total of 751 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 12 papers in Artificial Intelligence. Recurrent topics in Prasenjit Mukherjee's work include Computational Drug Discovery Methods (14 papers), Topic Modeling (6 papers) and Natural Language Processing Techniques (6 papers). Prasenjit Mukherjee is often cited by papers focused on Computational Drug Discovery Methods (14 papers), Topic Modeling (6 papers) and Natural Language Processing Techniques (6 papers). Prasenjit Mukherjee collaborates with scholars based in United States, India and Switzerland. Prasenjit Mukherjee's co-authors include Ingo Muegge, Éric Martin, Prashant Desai, Mitchell A. Avery, Falgun Shah, Mitchell A. Avery, Baisakhi Chakraborty, Johanna M. Jansen, Babu L. Tekwani and David C. Sullivan and has published in prestigious journals such as Journal of Medicinal Chemistry, Current Medicinal Chemistry and Bioorganic & Medicinal Chemistry.

In The Last Decade

Prasenjit Mukherjee

45 papers receiving 732 citations

Peers

Prasenjit Mukherjee

CTM

PHEOH

Cleber C. Melo‐Filho United States

Maris Lapins Sweden

Alisson Marques da Silva Brazil

Daniel H. Foil United States

Andreas Schüller Germany

Eduardo Habib Bechelane Maia Brazil

Utkarsh Raj India

Michael Hsing Canada

Alfonso T. García‐Sosa Estonia

Salma Jamal India

Cleber C. Melo‐Filho United States

Prasenjit Mukherjee

424 ×1.0

CTM

313 ×0.8

157 ×1.5

115 ×1.1

PHEOH

124 ×1.2

Citations per year, relative to Prasenjit Mukherjee Prasenjit Mukherjee (= 1×) peers Cleber C. Melo‐Filho

Countries citing papers authored by Prasenjit Mukherjee

Since Specialization

Citations

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

Fields of papers citing papers by Prasenjit Mukherjee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Prasenjit Mukherjee

This figure shows the co-authorship network connecting the top 25 collaborators of Prasenjit Mukherjee. A scholar is included among the top collaborators of Prasenjit Mukherjee 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 Prasenjit Mukherjee. Prasenjit Mukherjee 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

Mukherjee, Prasenjit, Manish Godse, & Baisakhi Chakraborty. (2024). Detection of Autism Spectrum Disorder (ASD) Symptoms using LSTM Model. 21. 40–54. 1 indexed citations

Mukherjee, Prasenjit, et al.. (2023). Bengali Query Processing System for Disease Detection using LSTM and GRU. International Journal of Computing and Digital Systems. 14(1). 643–656. 1 indexed citations

Mukherjee, Prasenjit, et al.. (2023). Efficacy of Deep Neural Embeddings-Based Semantic Similarity in Automatic Essay Evaluation. International Journal of Cognitive Informatics and Natural Intelligence. 17(1). 1–14. 3 indexed citations

Mukherjee, Prasenjit, et al.. (2023). A Review of Machine Learning Models to Detect Autism Spectrum Disorders (ASD). 22. 177–189. 4 indexed citations

Mukherjee, Prasenjit, et al.. (2023). Examination of AI Algorithms for Image and MRI-based Autism Detection. 22. 243–252.

Mukherjee, Prasenjit, et al.. (2023). Bengali language-based Disease diagnosis system for rural people using Bidirectional Encoder Representations from Transformers. 1–6. 1 indexed citations

Mukherjee, Prasenjit, et al.. (2023). Detection of Autism Spectrum Disorder (ASD) from Natural Language Text using BERT and ChatGPT Models. International Journal of Advanced Computer Science and Applications. 14(10). 10 indexed citations

Mukherjee, Prasenjit, et al.. (2019). A novel Bengali Language Query Processing System (BLQPS) in medical domain. Intelligent Decision Technologies. 13(2). 177–192. 4 indexed citations

Martin, Éric, Valery Polyakov, Xiang‐Wei Zhu, et al.. (2019). All-Assay-Max2 pQSAR: Activity Predictions as Accurate as Four-Concentration IC ₅₀ s for 8558 Novartis Assays. Journal of Chemical Information and Modeling. 59(10). 4450–4459. 41 indexed citations

10.

Mukherjee, Prasenjit, et al.. (2018). Automated Generation of E-R Diagram from a Given Text in Natural Language. 91–96. 6 indexed citations

11.

Varnes, Jeffrey, Thomas W. Gero, Shan Huang, et al.. (2014). Towards the next generation of dual Bcl-2/Bcl-xL inhibitors. Bioorganic & Medicinal Chemistry Letters. 24(14). 3026–3033. 14 indexed citations

12.

Li, Tian, Prasenjit Mukherjee, & Éric Martin. (2013). Kinase‐Kernel Models: Accurate Chemogenomic Method for the Entire Human Kinome. Molecular Informatics. 32(11-12). 922–928. 1 indexed citations

13.

Mukherjee, Prasenjit & Éric Martin. (2011). Development of a Minimal Kinase Ensemble Receptor (MKER) for Surrogate AutoShim. Journal of Chemical Information and Modeling. 51(10). 2697–2705. 2 indexed citations

14.

Pradhan, Anupam, Abhai K. Tripathi, Prashant Desai, et al.. (2009). Structure and function of Plasmodium falciparum malate dehydrogenase: Role of critical amino acids in co-substrate binding pocket. Biochimie. 91(11-12). 1509–1517. 13 indexed citations

15.

Shah, Falgun, Shuang‐Qing Zhang, Prasenjit Mukherjee, et al.. (2009). In vitro erythrocytic uptake studies of artemisinin and selected derivatives using LC–MS and 2D-QSAR analysis of uptake in parasitized erythrocytes. Bioorganic & Medicinal Chemistry. 17(14). 5325–5331. 9 indexed citations

16.

Pradhan, Anupam, Prasenjit Mukherjee, Abhai K. Tripathi, et al.. (2009). Analysis of quaternary structure of a [LDH-like] malate dehydrogenase of Plasmodium falciparum with oligomeric mutants. Molecular and Cellular Biochemistry. 325(1-2). 141–148. 8 indexed citations

17.

Srivastava, Anuradha, Prasenjit Mukherjee, Prashant Desai, Mitchell A. Avery, & Babu L. Tekwani. (2008). Structural Analysis of Farnesyl Pyrophosphate Synthase from Parasitic Protozoa, a Potential Chemotherapeutic Target. Infectious Disorders - Drug Targets. 8(1). 16–30. 9 indexed citations

18.

Mukherjee, Prasenjit, Prashant Desai, Larry J. Ross, E. Lucile White, & Mitchell A. Avery. (2008). Structure-based virtual screening against SARS-3CLpro to identify novel non-peptidic hits. Bioorganic & Medicinal Chemistry. 16(7). 4138–4149. 38 indexed citations

19.

Choi, Seoung‐ryoung, et al.. (2008). The Fight Against Drug-Resistant Malaria: Novel Plasmodial Targets and Antimalarial Drugs. Current Medicinal Chemistry. 15(2). 161–171. 28 indexed citations

20.

Ghoshal, Nanda & Prasenjit Mukherjee. (2003). 3-D-QSAR of N-substituted 4-amino-3,3-dialkyl-2(3H)-furanone GABA receptor modulators using molecular field analysis and receptor surface modelling study. Bioorganic & Medicinal Chemistry Letters. 14(1). 103–109. 13 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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