S. Jagadish

947 citations
11 papers · 686 · h-index 7

Impact in

Papers in

S. Jagadish

10 papers receiving 668 citations

Peers

S. Jagadish
Comparison fields: 5 of 58
  • Cellular and Molecular Neuroscience 500
  • Aging 26
  • Endocrine and Autonomic Systems 48
  • Molecular Biology 408
  • Neurology 76
Replace Ulrike Pech with:
Ulrike Pech Germany
Daniel T. Babcock United States
Marlène Cassar United States
Lisa Scheunemann Germany
John B. Connolly United Kingdom
Anna Grygoruk United States
Meg A. Younger United States
Stefanie Schirmeier Germany
Sudipta Saraswati United States
Sudeshna Das Chakraborty Germany
S. Jagadish relative to Ulrike Pech Germany Ulrike Pech's profile →
Citations per field
00.5×2.8×
Ulrike Pech · 1×
Citations per year

Countries citing papers authored by S. Jagadish

Since Specialization
Citations

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

Fields of papers citing papers by S. Jagadish

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside S. Jagadish, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with S. Jagadish Line = papers co-authored together S. Jagadish links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 2006239
2 2012226
3 2006133
4 201434
5 202026
6
Antibiogram and treatment of bovine sub-clinical mastitis.
200010
7 19907
8
Evaluation of some byre-side tests in bovine sub-clinical mastitis.
20005
9 20124
10
Neonatal calf diarrhoea : serotyping of E.coli isolates.
20001
11
Immunization against bovine tropical theileriosis, using 60Co-irradiated infective particles of Theileria annulata (Dschunkowsky and Luhs 1904) derived from ticks.
19791

About S. Jagadish

S. Jagadish is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Small Animals, Endocrine and Autonomic Systems and Agronomy and Crop Science, having authored 11 papers that have together received 686 indexed citations. Recurring topics across this work include Circadian rhythm and melatonin (2 papers), Mitochondrial Function and Pathology (2 papers), Fungal and yeast genetics research (2 papers), Neurobiology and Insect Physiology Research (2 papers), Genetic Neurodegenerative Diseases (2 papers), Insect and Pesticide Research (2 papers), Milk Quality and Mastitis in Dairy Cows (2 papers) and Adipose Tissue and Metabolism (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (500 citations), Aging (26 citations), Endocrine and Autonomic Systems (48 citations), Molecular Biology (408 citations) and Neurology (76 citations). S. Jagadish has collaborated with scholars based in United States, India and France. Frequent co-authors include Susan Lindquist, Martin L. Duennwald, Paul J. Muchowski, Gilad Barnea, Richard Axel, Flaviano Giorgini, H. Inagaki, Toshihiro Kitamoto, Allan M. Wong and David J. Anderson. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences, Journal of Veterinary Pharmacology and Therapeutics, Neuron and JCI Insight.

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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