Laxman S. Meena

1.2k citations
58 papers · 897 indexed · h-index 18

Laxman S. Meena

56 papers receiving 865 citations

Peers

Laxman S. Meena
Comparison fields: 5 of 78
  • Infectious Diseases 490
  • Biotechnology 156
  • Molecular Medicine 48
  • Endocrinology 43
  • Epidemiology 271
Replace Veeraraghavan Usha with:
Veeraraghavan Usha United Kingdom
Shannon Caldwell United States
Eusondia Arnett United States
Wonsik Lee South Korea
Karolin Biermann United States
Cíntia Renata Costa Rocha Brazil
Christian Chalut France
Krishan Gopal Thakur India
Radhika Gupta India
Damien Portevin Switzerland
Laxman S. Meena relative to Veeraraghavan Usha United Kingdom Veeraraghavan Usha's profile →
Citations per field
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Veeraraghavan Usha · 1×
Citations per year

Countries citing papers authored by Laxman S. Meena

Since Specialization
Citations

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

Fields of papers citing papers by Laxman S. Meena

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laxman S. Meena. 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 Laxman S. Meena. The network helps show where Laxman S. Meena may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Laxman S. Meena, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Laxman S. Meena Line = papers co-authored together Laxman S. Meena links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20216
3 20210
4 20215
5 20211
6 20216
7 20202
8 20204
9
Cholesterol Metabolism: As a Promising Target Candidate for Tuberculosis Treatment by Nanomedicine
20202
10 20192
11
In silico Screening of Protein Rv3228 to have a Vision towards Survival and Pathogenesis of Mycobacterium tuberculosis H37Rv
20191
12 201837
13 201817
14 20157
15 201111
16 2010158
17 200825
18 200720
19 200287
20 200211

About Laxman S. Meena

Laxman S. Meena is a scholar working on Infectious Diseases, Molecular Medicine and Physiology, having authored 58 papers that have together received 897 indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (43 papers), Mycobacterium research and diagnosis (15 papers), Pneumocystis jirovecii pneumonia detection and treatment (10 papers), Biochemical and Molecular Research (9 papers), RNA and protein synthesis mechanisms (7 papers), vaccines and immunoinformatics approaches (5 papers), Bacterial Genetics and Biotechnology (5 papers) and Computational Drug Discovery Methods (4 papers). The work is most often cited by research in Infectious Diseases (490 citations), Biotechnology (156 citations) and Molecular Medicine (48 citations). Laxman S. Meena has collaborated with scholars based in India and United States. Frequent co-authors include Rajni Rajni, Yogendra Singh, Puneet Chopra, Akhilesh K. Tyagi, Dewal Jani, Arun Kumar Sharma, Priyanka Kumari, Ranveer Singh Bedwal, Sonu Chand Thakur and Nirmal Kumar Singh. Their work appears in journals such as SHILAP Revista de lepidopterología, Biochemical and Biophysical Research Communications and International Journal of Biological Macromolecules.

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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