Nandini Krishnamurthy

962 total citations
13 papers, 683 citations indexed

About

Nandini Krishnamurthy is a scholar working on Molecular Biology, Plant Science and Genetics. According to data from OpenAlex, Nandini Krishnamurthy has authored 13 papers receiving a total of 683 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Plant Science and 1 paper in Genetics. Recurrent topics in Nandini Krishnamurthy's work include Genomics and Phylogenetic Studies (7 papers), Machine Learning in Bioinformatics (4 papers) and Bioinformatics and Genomic Networks (3 papers). Nandini Krishnamurthy is often cited by papers focused on Genomics and Phylogenetic Studies (7 papers), Machine Learning in Bioinformatics (4 papers) and Bioinformatics and Genomic Networks (3 papers). Nandini Krishnamurthy collaborates with scholars based in United States, Switzerland and Belgium. Nandini Krishnamurthy's co-authors include Kimmen Sjölander, Lillian K. Fritz‐Laylin, Jonathan D. G. Jones, Mahmut Tör, Brian J. Staskawicz, Stephen T. Chisholm, Brad Day, Douglas Dahlbeck, D. Brown and Sacha Baginsky and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Nandini Krishnamurthy

13 papers receiving 671 citations

Peers

Nandini Krishnamurthy
Nandini Krishnamurthy
Citations per year, relative to Nandini Krishnamurthy Nandini Krishnamurthy (= 1×) peers Anne‐Marie Duchêne

Countries citing papers authored by Nandini Krishnamurthy

Since Specialization
Citations

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

Fields of papers citing papers by Nandini Krishnamurthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nandini Krishnamurthy

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

All Works

13 of 13 papers shown
1.
Dewachter, Liselot, Aaron N. Brooks, Nandini Krishnamurthy, et al.. (2023). Deep mutational scanning of essential bacterial proteins can guide antibiotic development. Nature Communications. 14(1). 241–241. 24 indexed citations
2.
Krishnamurthy, Nandini, Caitlyn Ngam, Anthony J. Berdis, & Monica M. Montano. (2011). The exonuclease activity of hPMC2 is required for transcriptional regulation of the QR gene and repair of estrogen-induced abasic sites. Oncogene. 30(47). 4731–4739. 10 indexed citations
3.
Wanchana, Samart, Supat Thongjuea, Victor Jun Ulat, et al.. (2007). The Generation Challenge Programme comparative plant stress-responsive gene catalogue. Nucleic Acids Research. 36(suppl_1). D943–D946. 5 indexed citations
4.
Krishnamurthy, Nandini, et al.. (2007). Automated Protein Subfamily Identification and Classification. PLoS Computational Biology. 3(8). e160–e160. 89 indexed citations
5.
Krishnamurthy, Nandini, D. Brown, & Kimmen Sjölander. (2007). FlowerPower: clustering proteins into domain architecture classes for phylogenomic inference of protein function. BMC Evolutionary Biology. 7(S1). S12–S12. 45 indexed citations
6.
Krishnamurthy, Nandini, et al.. (2006). PhyloFacts: an online structural phylogenomic encyclopedia for protein functional and structural classification. Genome biology. 7(9). R83–R83. 43 indexed citations
7.
Zychlinski, Anne von, Torsten Kleffmann, Nandini Krishnamurthy, et al.. (2005). Proteome Analysis of the Rice Etioplast. Molecular & Cellular Proteomics. 4(8). 1072–1084. 98 indexed citations
8.
Krishnamurthy, Nandini, et al.. (2005). Basic Protein Sequence Analysis. Current Protocols in Protein Science. 41(1). 2.11.1–2.11.24. 1 indexed citations
9.
Fritz‐Laylin, Lillian K., et al.. (2005). Phylogenomic Analysis of the Receptor-Like Proteins of Rice and Arabidopsis. PLANT PHYSIOLOGY. 138(2). 611–623. 180 indexed citations
10.
Chisholm, Stephen T., Douglas Dahlbeck, Nandini Krishnamurthy, et al.. (2005). Molecular characterization of proteolytic cleavage sites of the Pseudomonas syringae effector AvrRpt2. Proceedings of the National Academy of Sciences. 102(6). 2087–2092. 121 indexed citations
11.
Sjölander, Kimmen, et al.. (2005). Predicted hexameric structure of theAgrobacteriumVirB4 C terminus suggests VirB4 acts as a docking site during type IV secretion. Proceedings of the National Academy of Sciences. 102(5). 1685–1690. 48 indexed citations
12.
Krishnamurthy, Nandini & Kimmen Sjölander. (2005). Phylogenomic Inference of Protein Molecular Function. Current Protocols in Bioinformatics. 11(1). Unit 6.9–Unit 6.9. 3 indexed citations
13.
Brown, D., et al.. (2004). SUBFAMILY HMMS IN FUNCTIONAL GENOMICS. PubMed. 322–333. 16 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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