Manish Kumar

4.5k total citations · 1 hit paper
103 papers, 3.2k citations indexed

About

Manish Kumar is a scholar working on Molecular Biology, Molecular Medicine and Genetics. According to data from OpenAlex, Manish Kumar has authored 103 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Molecular Biology, 19 papers in Molecular Medicine and 17 papers in Genetics. Recurrent topics in Manish Kumar's work include Machine Learning in Bioinformatics (28 papers), Genomics and Phylogenetic Studies (25 papers) and RNA and protein synthesis mechanisms (21 papers). Manish Kumar is often cited by papers focused on Machine Learning in Bioinformatics (28 papers), Genomics and Phylogenetic Studies (25 papers) and RNA and protein synthesis mechanisms (21 papers). Manish Kumar collaborates with scholars based in India, Canada and United States. Manish Kumar's co-authors include Neelja Singhal, Jugsharan Singh Virdi, Gajendra P. S. Raghava, Pawan Kumar Kanaujia, M. Michael Gromiha, Ravindra Kumar, Bandana Kumari, Ruchi Verma, Shilpa Mohanty and Paul M. Harrison and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Manish Kumar

99 papers receiving 3.1k citations

Hit Papers

MALDI-TOF mass spectrometry: an emerging technology for m... 2015 2026 2018 2022 2015 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. MALDI-TOF mass spectrometry: an emerging technology for microbial identification and diagnosis
    2015 1.1k citations Neelja Singhal, Manish Kumar et al. Frontiers in Microbiology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Manish Kumar India 26 2.0k 465 344 292 257 103 3.2k
Matthew W. Frank United States 30 1.7k 0.8× 201 0.4× 470 1.4× 444 1.5× 171 0.7× 63 2.9k
Ralf Dieckmann Germany 32 1.0k 0.5× 421 0.9× 191 0.6× 145 0.5× 438 1.7× 73 2.5k
István Nagy Hungary 29 1.3k 0.7× 195 0.4× 324 0.9× 167 0.6× 107 0.4× 92 3.1k
Joshua T. Thaden United States 25 1.4k 0.7× 400 0.9× 460 1.3× 483 1.7× 97 0.4× 60 2.9k
Vincent M. Isabella United States 19 1.7k 0.9× 138 0.3× 173 0.5× 394 1.3× 295 1.1× 31 2.8k
Thomas Maier Germany 29 1.0k 0.5× 1.1k 2.4× 676 2.0× 264 0.9× 105 0.4× 54 2.7k
James E. Bray United Kingdom 27 1.9k 1.0× 122 0.3× 415 1.2× 261 0.9× 342 1.3× 65 3.0k
Jeremy P. Derrick United Kingdom 34 2.8k 1.4× 150 0.3× 575 1.7× 482 1.7× 117 0.5× 119 4.3k
George Y. Liu United States 39 2.4k 1.2× 318 0.7× 794 2.3× 1.7k 5.8× 262 1.0× 78 6.0k
Gerald Larrouy‐Maumus United Kingdom 28 1.2k 0.6× 279 0.6× 680 2.0× 677 2.3× 111 0.4× 87 2.4k

Countries citing papers authored by Manish Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Manish Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manish Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Manish Kumar. A scholar is included among the top collaborators of Manish Kumar 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 Manish Kumar. Manish Kumar 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.
2.
Singhal, Neelja, et al.. (2023). β-LacFamPred: An online tool for prediction and classification of β-lactamase class, subclass, and family. Frontiers in Microbiology. 13. 1039687–1039687. 1 indexed citations
3.
Akhtar, Nahid, et al.. (2023). Potent antifungal properties of gallic acid in Sarcochlamys pulcherrima against Candida auris. SHILAP Revista de lepidopterología. 104(2). 105–119. 8 indexed citations
4.
Tiwari, Mayank, et al.. (2023). Inbuilt Chat GPT Feature in Smartwatches. 1806–1813. 2 indexed citations
5.
Bhardwaj, Kanchan, et al.. (2022). Insights into the human gut virome by sampling a population from the Indian subcontinent. Journal of General Virology. 103(8). 4 indexed citations
6.
Dhasarathan, Chandramohan, et al.. (2022). COVID-19 identification in chest X-ray images using intelligent multi-level classification scenario. Computers & Electrical Engineering. 104. 108405–108405. 11 indexed citations
7.
Singhal, Neelja, et al.. (2021). Investigating the OXA Variants of ESKAPE Pathogens. Antibiotics. 10(12). 1539–1539. 11 indexed citations
8.
9.
Akhtar, Nahid, Amit Joshi, Vikas Kaushik, Manish Kumar, & M. Amin‐ul Mannan. (2021). In-silico design of a multivalent epitope-based vaccine against Candida auris. Microbial Pathogenesis. 155. 104879–104879. 48 indexed citations
10.
11.
Kumar, Manish, et al.. (2018). Silver nanoparticles induced alterations in multiple cellular targets, which are critical for drug susceptibilities and pathogenicity in fungal pathogen (Candida albicans). SHILAP Revista de lepidopterología. 4 indexed citations
12.
Kumari, Bandana, et al.. (2018). Using molecular-mimicry-inducing pathways of pathogens as novel drug targets. Drug Discovery Today. 24(9). 1943–1952. 7 indexed citations
13.
Kumar, Manish, et al.. (2016). CrAgDb—a database of annotatedchaperonerepertoire inarchaealgenomes. FEMS Microbiology Letters. 363(6). fnw030–fnw030. 8 indexed citations
14.
Singhal, Neelja, Manish Kumar, Divakar Sharma, & Deepa Bisht. (2015). Comparative Protein Profiling of Intraphagosomal Expressed Proteins of Mycobacterium bovis BCG. Protein and Peptide Letters. 23(1). 51–54. 4 indexed citations
15.
Kumari, Bandana, Ravindra Kumar, & Manish Kumar. (2014). Low complexity and disordered regions of proteins have different structural and amino acid preferences. Molecular BioSystems. 11(2). 585–594. 31 indexed citations
16.
Kumari, Bandana, Ravindra Kumar, & Manish Kumar. (2014). PalmPred: An SVM Based Palmitoylation Prediction Method Using Sequence Profile Information. PLoS ONE. 9(2). e89246–e89246. 50 indexed citations
17.
Marimuthu, Parthiban, Deena M.A. Gendoo, Sepehr Ehsani, et al.. (2012). PrionHome: A Database of Prions and Other Sequences Relevant to Prion Phenomena. PLoS ONE. 7(2). e31785–e31785. 21 indexed citations
18.
Harrison, Paul M., Amit N. Khachane, & Manish Kumar. (2010). Genomic assessment of the evolution of the prion protein gene family in vertebrates. Genomics. 95(5). 268–277. 30 indexed citations
19.
Kumar, Manish, M. Michael Gromiha, & Gajendra P. S. Raghava. (2007). Prediction of RNA binding sites in a protein using SVM and PSSM profile. Proteins Structure Function and Bioinformatics. 71(1). 189–194. 230 indexed citations
20.
Kumar, Manish, et al.. (2005). BhairPred: prediction of  -hairpins in a protein from multiple alignment information using ANN and SVM techniques. Nucleic Acids Research. 33(Web Server). W154–W159. 58 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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