Daniel B. Forger

87 papers receiving 4.1k citations

Peers

Daniel B. Forger
Comparison fields: 5 of 138
  • Endocrine and Autonomic Systems 2.5k
  • Aging 201
  • Experimental and Cognitive Psychology 767
  • Cellular and Molecular Neuroscience 936
  • Cognitive Neuroscience 950
Replace Steven M. Reppert with:
Steven M. Reppert United States
David K. Welsh United States
Tanya Leise United States
Sooyoung Chung South Korea
Jude F. Mitchell United States
Sean Hill Switzerland
Petra E. Vértes United Kingdom
Jeffrey C. Smith United States
Donald Cooper United States
James S. Schwaber United States
Daniel B. Forger relative to Steven M. Reppert United States Steven M. Reppert's profile →
Citations per field
00.5×10×14.5×
Steven M. Reppert · 1×
Citations per year

Countries citing papers authored by Daniel B. Forger

Since Specialization
Citations

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

Fields of papers citing papers by Daniel B. Forger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel B. Forger. 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 Daniel B. Forger. The network helps show where Daniel B. Forger may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003276
2 2019180
3 2012178
4 2016174
5 2010171
6 1999162
7 2006148
8 2009144
9 2015144
10 2004144
11 2015138
12 1999132
13 1999132
14 2018125
15 2014117
16 2015117
17 200688
18 200784
19 201480
20 200972

About Daniel B. Forger

Daniel B. Forger is a scholar working on Endocrine and Autonomic Systems, Cellular and Molecular Neuroscience, Cognitive Neuroscience, Experimental and Cognitive Psychology and Plant Science, having authored 90 papers that have together received 4.2k indexed citations. Recurring topics across this work include Circadian rhythm and melatonin (56 papers), Photoreceptor and optogenetics research (19 papers), Light effects on plants (17 papers), Neural dynamics and brain function (11 papers), Gene Regulatory Network Analysis (11 papers), Sleep and related disorders (10 papers), Sleep and Wakefulness Research (8 papers) and Spaceflight effects on biology (8 papers). The work is most often cited by research in Endocrine and Autonomic Systems (2.5k citations), Aging (201 citations), Experimental and Cognitive Psychology (767 citations), Cellular and Molecular Neuroscience (936 citations) and Cognitive Neuroscience (950 citations). Daniel B. Forger has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Charles S. Peskin, Richard E. Kronauer, Megan E. Jewett, Jae Kyoung Kim, Olivia Walch, David M. Virshup, David Paydarfar, Yitong Huang, Amy L. Cochran and Cathy Goldstein. Their work appears in journals such as Journal of Biological Rhythms, Proceedings of the National Academy of Sciences, PLoS Computational Biology, PLoS Biology and SLEEP.

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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