I. Nir

55 papers receiving 991 citations

Peers

I. Nir
Comparison fields: 5 of 100
  • Endocrine and Autonomic Systems 424
  • Aging 26
  • Cognitive Neuroscience 282
  • Cellular and Molecular Neuroscience 210
  • Biological Psychiatry 24
Replace Laurence A. Brown with:
Laurence A. Brown United Kingdom
Hing-Sing Yu Hong Kong
Aarti Jagannath United Kingdom
S.F. Pang Hong Kong
Ario Conti Switzerland
N Bons France
Jorge M. Rosner Argentina
Bernard Possidente United States
Keisuke Ikegami Japan
Robin A. Barraco United States
I. Nir relative to Laurence A. Brown United Kingdom Laurence A. Brown's profile →
Citations per field
00.5×1.5×
Laurence A. Brown · 1×
Citations per year

Countries citing papers authored by I. Nir

Since Specialization
Citations

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

Fields of papers citing papers by I. Nir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside I. Nir, 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 I. Nir Line = papers co-authored together I. Nir links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995172
2 198896
3 200980
4 198868
5 199558
6 196952
7 196948
8 198441
9 199136
10 196426
11 197524
12 197223
13 198821
14 198920
15 197020
16 197819
17 197818
18 196917
19 195916
20 197615

About I. Nir

I. Nir is a scholar working on Endocrine and Autonomic Systems, Animal Science and Zoology, Cellular and Molecular Neuroscience, Physiology and Endocrinology, Diabetes and Metabolism, having authored 55 papers that have together received 1.0k indexed citations. Recurring topics across this work include Circadian rhythm and melatonin (17 papers), Animal Nutrition and Physiology (7 papers), Adipose Tissue and Metabolism (5 papers), Sleep and Wakefulness Research (5 papers), Peroxisome Proliferator-Activated Receptors (4 papers), Birth, Development, and Health (4 papers), Growth Hormone and Insulin-like Growth Factors (4 papers) and Photoreceptor and optogenetics research (4 papers). The work is most often cited by research in Endocrine and Autonomic Systems (424 citations), Aging (26 citations), Cognitive Neuroscience (282 citations), Cellular and Molecular Neuroscience (210 citations) and Biological Psychiatry (24 citations). I. Nir has collaborated with scholars based in Israel, United States and Netherlands. Frequent co-authors include Nava Zisapel, Moshe Laudon, F.G. Sulman, Haim Y. Knobler, Yaacov Lerner, Samuel Lepkovsky, N. Snapir, F. Furuta, Jan M. van Ree and Raymond J.M. Niesink. Their work appears in journals such as Journal of Neural Transmission, Neuroendocrinology, Cellular and Molecular Life Sciences, British Journal of Cancer and Life Sciences.

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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