Shahla Gharib

483 total citations
9 papers, 350 citations indexed

About

Shahla Gharib is a scholar working on Aging, Endocrine and Autonomic Systems and Molecular Biology. According to data from OpenAlex, Shahla Gharib has authored 9 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Aging, 7 papers in Endocrine and Autonomic Systems and 3 papers in Molecular Biology. Recurrent topics in Shahla Gharib's work include Genetics, Aging, and Longevity in Model Organisms (9 papers), Circadian rhythm and melatonin (7 papers) and Gene Regulatory Network Analysis (2 papers). Shahla Gharib is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (9 papers), Circadian rhythm and melatonin (7 papers) and Gene Regulatory Network Analysis (2 papers). Shahla Gharib collaborates with scholars based in United States and Switzerland. Shahla Gharib's co-authors include Paul W. Sternberg, Carol Bastiani, Melvin I. Simon, Wendy S. Katz, Rashmi Deshpande, Russell J. Hill, Helieh S. Oz, Takao Inoue, Han Wang and Jonathan Liu and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nature Methods.

In The Last Decade

Shahla Gharib

8 papers receiving 344 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shahla Gharib United States 6 242 163 126 68 40 9 350
Gopal Battu Switzerland 5 176 0.7× 197 1.2× 77 0.6× 28 0.4× 59 1.5× 5 355
Zeynep F. Altun United States 11 302 1.2× 178 1.1× 135 1.1× 94 1.4× 10 0.3× 32 431
Brinda C. Prasad United States 7 182 0.8× 233 1.4× 77 0.6× 156 2.3× 17 0.4× 10 451
Howard C. Chang United States 9 156 0.6× 269 1.7× 65 0.5× 52 0.8× 7 0.2× 15 434
Nikolaos Stefanakis United States 6 128 0.5× 174 1.1× 46 0.4× 60 0.9× 12 0.3× 6 265
Don Moerman Canada 5 196 0.8× 196 1.2× 39 0.3× 41 0.6× 21 0.5× 8 351
T Blumenthal United States 13 383 1.6× 347 2.1× 106 0.8× 23 0.3× 55 1.4× 37 541
Andrew B Hellman United States 6 303 1.3× 357 2.2× 95 0.8× 41 0.6× 8 0.2× 7 684
Yingsong Hao United States 7 288 1.2× 218 1.3× 88 0.7× 40 0.6× 56 1.4× 7 415
Robert Steven Canada 9 226 0.9× 335 2.1× 98 0.8× 248 3.6× 41 1.0× 9 615

Countries citing papers authored by Shahla Gharib

Since Specialization
Citations

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

Fields of papers citing papers by Shahla Gharib

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shahla Gharib

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

All Works

9 of 9 papers shown
1.
Gharib, Shahla, Han Wang, Jasmin S. Revanna, et al.. (2023). A cGAL-UAS bipartite expression toolkit for Caenorhabditis elegans sensory neurons. Proceedings of the National Academy of Sciences. 120(51). e2221680120–e2221680120. 3 indexed citations
2.
Kato, Mihoko, Irina Kolotuev, Alexandre Cunha, Shahla Gharib, & Paul W. Sternberg. (2020). Extrasynaptic acetylcholine signaling through a muscarinic receptor regulates cell migration. Proceedings of the National Academy of Sciences. 118(1). 12 indexed citations
3.
Gharib, Shahla, et al.. (2019). DVC interneuron cGAL driver in Caenorhabditis elegans. PubMed. 2019. 1 indexed citations
4.
5.
Wang, Han, Jonathan Liu, Shahla Gharib, et al.. (2016). cGAL, a temperature-robust GAL4–UAS system for Caenorhabditis elegans. Nature Methods. 14(2). 145–148. 50 indexed citations
6.
Yu, Hui, Boanerges Aleman-Meza, Shahla Gharib, et al.. (2013). Systematic profiling of C aenorhabditis elegans locomotive behaviors reveals additional components in G-protein Gαq signaling. Proceedings of the National Academy of Sciences. 110(29). 11940–11945. 22 indexed citations
7.
Schindelman, Gary, et al.. (2006). Initiation of male sperm-transfer behavior in Caenorhabditis elegansrequires input from the ventral nerve cord. BMC Biology. 4(1). 26–26. 32 indexed citations
8.
Inoue, Takao, Helieh S. Oz, Shahla Gharib, et al.. (2004). C. elegans LIN-18 Is a Ryk Ortholog and Functions in Parallel to LIN-17/Frizzled in Wnt Signaling. Cell. 118(6). 795–806. 150 indexed citations
9.
Bastiani, Carol, Shahla Gharib, Melvin I. Simon, & Paul W. Sternberg. (2003). Caenorhabditis elegans Gαq Regulates Egg-Laying Behavior via a PLCβ-Independent and Serotonin-Dependent Signaling Pathway and Likely Functions Both in the Nervous System and in Muscle. Genetics. 165(4). 1805–1822. 80 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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