Prabha Garg

2.2k citations
111 papers · 1.6k indexed · h-index 24
Topics
Computational Drug Discovery Methods (40 papers)Biochemical and Molecular Research (11 papers)Cholinesterase and Neurodegenerative Diseases (10 papers)
Partner nations
IndiaSwedenUnited States

In The Last Decade

Prabha Garg

99 papers receiving 1.6k citations

Peers

Prabha Garg
Comparison fields: 5 of 136
  • Molecular Biology 681
  • Computational Theory and Mathematics 448
  • Organic Chemistry 251
  • Pharmacology 180
  • Oncology 164
Replace Vinícius Gonçalves Maltarollo with:
Vinícius Gonçalves Maltarollo Brazil
Naidu Subbarao India
Karthikeyan Muthusamy India
Teck Kwang Lim Singapore
Vivek K. Vyas India
Hongmao Sun United States
Peng Sang China
Massimo Baroni Italy
David Lagorce France
Youyou Tu China
Prabha Garg relative to Vinícius Gonçalves Maltarollo Brazil Vinícius Gonçalves Maltarollo's profile →
Citations per field
00.5×1.7×
Vinícius Gonçalves Maltarollo · 1×
Citations per year

Countries citing papers authored by Prabha Garg

Since Specialization
Citations

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

Fields of papers citing papers by Prabha Garg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Prabha Garg

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 3
2 0
3 1
4 0
5 0
6 11
7 23
8 9
9 0
10 14
11 36
12 7
13 29
14 14
15 9
16 7
17 9
18 33
19 29
20
QSAR modeling of CCR5 receptor antagonists using artificial neural network
1

About Prabha Garg

Prabha Garg is a scholar working on Computational Theory and Mathematics, Virology and Pharmacology, having authored 111 papers that have together received 1.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (40 papers), Biochemical and Molecular Research (11 papers) and Cholinesterase and Neurodegenerative Diseases (10 papers). The work is most often cited by research in Computational Theory and Mathematics (448 citations), Virology (60 citations) and Pharmacology (95 citations). Prabha Garg has collaborated with scholars based in India, Sweden and United States. Frequent co-authors include Rajender Kumar, Jitender Verma, Pawan Gupta, Navneet Kumar, Hardeep Sandhu, Nilanjan Roy, Mahesh C. Sharma, Inder Pal Singh, Prasad V. Bharatam and Anju Sharma. Their work appears in journals such as Nucleic Acids Research, The Journal of Physical Chemistry B and Bioresource Technology.

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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