Srinivas Bandaru

1.1k total citations
49 papers, 822 citations indexed

About

Srinivas Bandaru is a scholar working on Molecular Biology, Computational Theory and Mathematics and Physiology. According to data from OpenAlex, Srinivas Bandaru has authored 49 papers receiving a total of 822 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 12 papers in Computational Theory and Mathematics and 8 papers in Physiology. Recurrent topics in Srinivas Bandaru's work include Computational Drug Discovery Methods (12 papers), Pharmacological Effects and Assays (7 papers) and Asthma and respiratory diseases (6 papers). Srinivas Bandaru is often cited by papers focused on Computational Drug Discovery Methods (12 papers), Pharmacological Effects and Assays (7 papers) and Asthma and respiratory diseases (6 papers). Srinivas Bandaru collaborates with scholars based in India, Japan and United States. Srinivas Bandaru's co-authors include Anuraj Nayarisseri, Sanjeev Kumar Singh, Mukesh Yadav, Amandeep Girdhar, Someswar Rao Sagurthi, Mallika Alvala, Tajamul Hussain, S. Sureshkumar, A. Jyothy and Tushar Banerjee and has published in prestigious journals such as PLoS ONE, Scientific Reports and Science Advances.

In The Last Decade

Srinivas Bandaru

48 papers receiving 809 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Srinivas Bandaru India 20 400 225 161 113 82 49 822
Annemette Thougaard Denmark 19 504 1.3× 81 0.4× 355 2.2× 46 0.4× 66 0.8× 30 1.2k
Mohammad Sarwar Jamal Saudi Arabia 19 467 1.2× 38 0.2× 203 1.3× 71 0.6× 130 1.6× 37 992
Nelson José Freitas da Silveira Brazil 15 438 1.1× 147 0.7× 142 0.9× 58 0.5× 46 0.6× 47 718
Anja Wilmes Austria 22 699 1.7× 45 0.2× 192 1.2× 87 0.8× 42 0.5× 45 1.3k
Xiaoling Xie China 17 387 1.0× 53 0.2× 183 1.1× 30 0.3× 232 2.8× 57 1.1k
Dimitrios Spiliotopoulos Switzerland 13 568 1.4× 116 0.5× 51 0.3× 69 0.6× 47 0.6× 24 735
Y. Yosaatmadja New Zealand 16 525 1.3× 83 0.4× 132 0.8× 97 0.9× 42 0.5× 20 791
Jay Chauhan United States 15 350 0.9× 42 0.2× 92 0.6× 199 1.8× 114 1.4× 27 695
Yibei Xiao China 16 377 0.9× 70 0.3× 250 1.6× 125 1.1× 134 1.6× 60 766
Shanhe Wan China 16 337 0.8× 52 0.2× 122 0.8× 172 1.5× 40 0.5× 44 678

Countries citing papers authored by Srinivas Bandaru

Since Specialization
Citations

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

Fields of papers citing papers by Srinivas Bandaru

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Srinivas Bandaru

This figure shows the co-authorship network connecting the top 25 collaborators of Srinivas Bandaru. A scholar is included among the top collaborators of Srinivas Bandaru 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 Srinivas Bandaru. Srinivas Bandaru 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
1.
Nayarisseri, Anuraj, Srinivas Bandaru, Khushboo Sharma, et al.. (2024). Epigenetic dysregulation in cancers by isocitrate dehydrogenase 2 (IDH2). Advances in protein chemistry and structural biology. 141. 223–253.
2.
Bandaru, Srinivas, Sai Peck Lee, Naoko Kumagai-Τakei, et al.. (2023). An RNA-immunoprecipitation via CRISPR/dCas13 reveals an interaction between the SARS-CoV-2 5'UTR RNA and the process of human lipid metabolism. Scientific Reports. 13(1). 10413–10413. 3 indexed citations
3.
Bandaru, Srinivas, Sai Peck Lee, Kei Yoshitome, et al.. (2020). Structure-based design of gRNA for Cas13. Scientific Reports. 10(1). 11610–11610. 42 indexed citations
4.
Bandaru, Srinivas, et al.. (2017). Molecular dynamic simulations reveal suboptimal binding of salbutamol in T164I variant of β2 adrenergic receptor. PLoS ONE. 12(10). e0186666–e0186666. 34 indexed citations
5.
Shukla, Ruchi, et al.. (2016). Structural basis for the in vitro known acyl-depsipeptide 2 (ADEP2) inhibition to Clp 2 protease from Mycobacterium tuberculosis. Bioinformation. 12(3). 92–97. 17 indexed citations
6.
Bandaru, Srinivas, et al.. (2016). Common SAR Derived from Multiple QSAR Models on Vorinostat Derivatives Targeting HDACs in Tumor Treatment. Current Pharmaceutical Design. 22(33). 5072–5078. 5 indexed citations
7.
8.
Bandaru, Srinivas, et al.. (2015). Molecular docking based screening of GABA (A) receptor inhibitors from plant derivatives. Bioinformation. 11(6). 280–289. 27 indexed citations
9.
10.
Bandaru, Srinivas, et al.. (2015). Identification of High Affinity Bioactive Salbutamol Conformer Directed Against Mutated (Thr164Ile) Beta 2 Adrenergic Receptor. Current Topics in Medicinal Chemistry. 15(1). 50–56. 22 indexed citations
11.
Shaheen, Uzma, A. Jyothy, Amandeep Girdhar, et al.. (2015). Computer aided identification of sodium channel blockers in the clinical treatment of epilepsy using molecular docking tools. Bioinformation. 11(3). 131–137. 22 indexed citations
12.
Dunna, Nageswara Rao, et al.. (2015). High Affinity Pharmacological Profiling of Dual Inhibitors Targeting RET and VEGFR2 in Inhibition of Kinase and Angiogeneis Events in Medullary Thyroid Carcinoma. Asian Pacific Journal of Cancer Prevention. 16(16). 7089–7095. 25 indexed citations
13.
Nischal, Anuradha, et al.. (2015). An In silico Approach for Identification of Novel Inhibitors as a Potential Therapeutics Targeting HIV-1 Viral Infectivity Factor. Current Topics in Medicinal Chemistry. 15(1). 65–72. 26 indexed citations
14.
Bandaru, Srinivas, et al.. (2015). Analysis of ADRB2 (Arg16Gly) Gene Variant with Susceptibility, Pharmacogenetic Response and Disease Severity in South Indian Asthmatics. Inflammation. 38(6). 2146–2155. 4 indexed citations
15.
Sagurthi, Someswar Rao, et al.. (2015). Molecular Docking studies of FKBP12-mTOR inhibitors using binding predictions. Bioinformation. 11(6). 307–315. 23 indexed citations
16.
Bhatia, Mayuri, Karnam Venkatesh, G. Ravi, et al.. (2014). Isolation and characterization of a novel chlorpyrifos degrading flavobacterium species EMBS0145 by 16S rRNA gene sequencing. Interdisciplinary Sciences Computational Life Sciences. 7(1). 1–6. 18 indexed citations
17.
Bandaru, Srinivas, et al.. (2014). Association of Transforming Growth Factor-Beta 1 Promoter Variant -509 C/T with Bronchial Asthma in South Indian Population. Inflammation. 38(1). 409–414. 2 indexed citations
18.
Bandaru, Srinivas, et al.. (2014). Alkyloxy carbonyl modified hexapeptides as a high affinity compounds for Wnt5A protein in the treatment of psoriasis. Bioinformation. 10(12). 743–749. 19 indexed citations
19.
Bandaru, Srinivas, et al.. (2013). Binding Modes and Pharmacophoric Features of Muscarinic Antagonism and β2 Agonism (MABA) Conjugates. Current Topics in Medicinal Chemistry. 13(14). 1650–1655. 17 indexed citations
20.
Bandaru, Srinivas, et al.. (2012). Immunotherapeutic Approach for Better Management of Cancer - Role of IL-18. Asian Pacific Journal of Cancer Prevention. 13(11). 5353–5361. 17 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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