Mala Murthy

7.3k total citations · 1 hit paper
44 papers, 2.4k citations indexed

About

Mala Murthy is a scholar working on Cellular and Molecular Neuroscience, Ecology, Evolution, Behavior and Systematics and Genetics. According to data from OpenAlex, Mala Murthy has authored 44 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Cellular and Molecular Neuroscience, 24 papers in Ecology, Evolution, Behavior and Systematics and 19 papers in Genetics. Recurrent topics in Mala Murthy's work include Neurobiology and Insect Physiology Research (32 papers), Animal Behavior and Reproduction (24 papers) and Insect and Arachnid Ecology and Behavior (19 papers). Mala Murthy is often cited by papers focused on Neurobiology and Insect Physiology Research (32 papers), Animal Behavior and Reproduction (24 papers) and Insect and Arachnid Ecology and Behavior (19 papers). Mala Murthy collaborates with scholars based in United States, Germany and Italy. Mala Murthy's co-authors include Talmo Pereira, Joshua W. Shaevitz, Thomas L. Schwarz, Philip Coen, Jan Clemens, Samuel S.‐H. Wang, Diego A. Pacheco, Diego Aldarondo, Lindsay Willmore and Mikhail Kislin and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Mala Murthy

42 papers receiving 2.4k citations

Hit Papers

Fast animal pose estimation using deep neural networks 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mala Murthy United States 26 1.1k 666 626 592 578 44 2.4k
Damon A. Clark United States 31 1.5k 1.3× 560 0.8× 248 0.4× 818 1.4× 424 0.7× 68 3.3k
Kristin Branson United States 24 1.3k 1.2× 851 1.3× 461 0.7× 714 1.2× 811 1.4× 39 4.2k
Arnim Jenett France 14 1.9k 1.7× 815 1.2× 273 0.4× 827 1.4× 1000 1.7× 21 2.9k
Michael B. Reiser United States 24 2.2k 1.9× 942 1.4× 246 0.4× 485 0.8× 842 1.5× 38 2.5k
Gwyneth M Card United States 21 1.5k 1.3× 803 1.2× 235 0.4× 280 0.5× 712 1.2× 37 2.0k
Eric D. Hoopfer United States 15 1.3k 1.2× 498 0.7× 246 0.4× 511 0.9× 590 1.0× 17 2.0k
Andrew Straw United States 27 1.5k 1.3× 1.1k 1.6× 186 0.3× 243 0.4× 774 1.3× 66 3.0k
Alice A. Robie United States 11 679 0.6× 507 0.8× 149 0.2× 181 0.3× 473 0.8× 15 1.4k
Pavan P Ramdya Switzerland 19 878 0.8× 323 0.5× 195 0.3× 353 0.6× 476 0.8× 30 1.6k
Amir Ayali Israel 29 1.3k 1.1× 528 0.8× 207 0.3× 282 0.5× 607 1.1× 123 2.5k

Countries citing papers authored by Mala Murthy

Since Specialization
Citations

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

Fields of papers citing papers by Mala Murthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mala Murthy

This figure shows the co-authorship network connecting the top 25 collaborators of Mala Murthy. A scholar is included among the top collaborators of Mala Murthy 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 Mala Murthy. Mala Murthy 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.
Baker, Christa A., et al.. (2024). The role of fruitless in specifying courtship behaviors across divergent Drosophila species. Science Advances. 10(11). eadk1273–eadk1273. 6 indexed citations
2.
Cowley, Benjamin R., et al.. (2024). Mapping model units to visual neurons reveals population code for social behaviour. Nature. 629(8014). 1100–1108. 12 indexed citations
3.
Matsliah, Arie, Szi-chieh Yu, Krzysztof Kruk, et al.. (2024). Neuronal parts list and wiring diagram for a visual system. Nature. 634(8032). 166–180. 21 indexed citations
4.
Pacheco, Diego A., et al.. (2023). Flexible circuit mechanisms for context-dependent song sequencing. Nature. 622(7984). 794–801. 16 indexed citations
5.
Pacheco, Diego A., Stephan Y. Thiberge, Eftychios A. Pnevmatikakis, & Mala Murthy. (2020). Auditory activity is diverse and widespread throughout the central brain of Drosophila. Nature Neuroscience. 24(1). 93–104. 29 indexed citations
6.
Calhoun, Adam J., Jonathan W. Pillow, & Mala Murthy. (2019). Unsupervised identification of the internal states that shape natural behavior. Nature Neuroscience. 22(12). 2040–2049. 104 indexed citations
7.
Deutsch, David, et al.. (2019). Shared Song Detector Neurons in Drosophila Male and Female Brains Drive Sex-Specific Behaviors. Current Biology. 29(19). 3200–3215.e5. 38 indexed citations
8.
Clemens, Jan, Nofar Ozeri-Engelhard, & Mala Murthy. (2018). Fast intensity adaptation enhances the encoding of sound in Drosophila. Nature Communications. 9(1). 134–134. 22 indexed citations
9.
Stern, David L., Jan Clemens, Philip Coen, et al.. (2017). Experimental and statistical reevaluation provides no evidence for Drosophila courtship song rhythms. Proceedings of the National Academy of Sciences. 114(37). 9978–9983. 10 indexed citations
10.
Crocker, Amanda, et al.. (2016). Cell-Type-Specific Transcriptome Analysis in the Drosophila Mushroom Body Reveals Memory-Related Changes in Gene Expression. Cell Reports. 15(7). 1580–1596. 57 indexed citations
11.
Coen, Philip & Mala Murthy. (2016). Singing on the fly: sensorimotor integration and acoustic communication in Drosophila. Current Opinion in Neurobiology. 38. 38–45. 22 indexed citations
12.
Coen, Philip, et al.. (2016). Sensorimotor Transformations Underlying Variability in Song Intensity during Drosophila Courtship. Neuron. 89(3). 629–644. 63 indexed citations
13.
Clemens, Jan, et al.. (2015). Connecting Neural Codes with Behavior in the Auditory System of Drosophila. Neuron. 87(6). 1332–1343. 46 indexed citations
14.
Sun, Xiaonan Richard, Aleksandra Badura, Diego A. Pacheco, et al.. (2013). Fast GCaMPs for improved tracking of neuronal activity. Nature Communications. 4(1). 2170–2170. 106 indexed citations
15.
Arthur, Benjamin, et al.. (2013). Multi-channel acoustic recording and automated analysis of Drosophila courtship songs. BMC Biology. 11(1). 11–11. 76 indexed citations
16.
Murthy, Mala, et al.. (2010). Sec5, a member of the exocyst complex, mediates Drosophila embryo cellularization. Development. 137(16). 2773–2783. 30 indexed citations
17.
Murthy, Mala. (2010). Unraveling the auditory system of Drosophila. Current Opinion in Neurobiology. 20(3). 281–287. 21 indexed citations
18.
Menon, Kaushiki P., Shane E. Andrews, Mala Murthy, Elizabeth R. Gavis, & Kai Zinn. (2009). The Translational Repressors Nanos and Pumilio Have Divergent Effects on Presynaptic Terminal Growth and Postsynaptic Glutamate Receptor Subunit Composition. Journal of Neuroscience. 29(17). 5558–5572. 55 indexed citations
19.
Murthy, Mala, Ila Fiete, & Gilles Laurent. (2008). Testing Odor Response Stereotypy in the Drosophila Mushroom Body. Neuron. 59(6). 1009–1023. 119 indexed citations
20.
Murthy, Mala, Dan Garza, Richard H. Scheller, & Thomas L. Schwarz. (2003). Mutations in the Exocyst Component Sec5 Disrupt Neuronal Membrane Traffic, but Neurotransmitter Release Persists. Neuron. 37(3). 433–447. 167 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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