Steven Chao

2.3k citations
32 papers · 972 · h-index 15

Impact in

Papers in

Steven Chao

31 papers receiving 959 citations

Peers

Steven Chao
Comparison fields: 5 of 95
  • Cellular and Molecular Neuroscience 421
  • Genetics 197
  • Cognitive Neuroscience 143
  • Hematology 73
  • Neurology 52
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R B Innis United States
Dipti V. Tillu United States
Maria Cristina D’Adamo Italy
Ilaria Guella Canada
Kim M. Hemsley Australia
Melissa B. Gingrich United States
María Martínez de Lagrán Spain
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Citations per field
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Citations per year

Countries citing papers authored by Steven Chao

Since Specialization
Citations

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

Fields of papers citing papers by Steven Chao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004220
2 1990114
3 2002108
4 200283
5 198863
6 200249
7 199241
8 199138
9 199036
10 201135
11 201225
12 200119
13 202017
14 198916
15 201314
16 201513
17 200612
18 201510
19
Enhanced specificity in immunoscreening of expression cDNA clones using radiolabeled antigen overlay.
198910
20 20197

About Steven Chao

Steven Chao is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Genetics, Psychiatry and Mental health and Physiology, having authored 32 papers that have together received 972 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (5 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (5 papers), Dementia and Cognitive Impairment Research (5 papers), Neurotransmitter Receptor Influence on Behavior (4 papers), Alzheimer's disease research and treatments (3 papers), Receptor Mechanisms and Signaling (3 papers), Mast cells and histamine (3 papers) and Biotin and Related Studies (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (421 citations), Genetics (197 citations), Cognitive Neuroscience (143 citations), Hematology (73 citations) and Neurology (52 citations). Steven Chao has collaborated with scholars based in United States, Brazil and Pakistan. Frequent co-authors include Marina E. Wolf, Julie Chao, Simona Mangiavacchi, Xiu Sun, Daniel A. Peterson, Marjorie A. Ariano, Lee Chao, William Xiong, Hey‐Kyoung Lee and Richard L. Huganir. Their work appears in journals such as American Journal of Roentgenology, Journal of Neurochemistry, EJNMMI Physics, Biochimica et Biophysica Acta (BBA) - General Subjects and Scientific Reports.

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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