Daniel Shih

1.9k total citations
42 papers, 1.5k citations indexed

About

Daniel Shih is a scholar working on Cell Biology, Genetics and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Daniel Shih has authored 42 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Cell Biology, 24 papers in Genetics and 17 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Daniel Shih's work include Hemoglobin structure and function (32 papers), Neonatal Health and Biochemistry (17 papers) and Hemoglobinopathies and Related Disorders (17 papers). Daniel Shih is often cited by papers focused on Hemoglobin structure and function (32 papers), Neonatal Health and Biochemistry (17 papers) and Hemoglobinopathies and Related Disorders (17 papers). Daniel Shih collaborates with scholars based in United States, United Kingdom and Taiwan. Daniel Shih's co-authors include M. F. Perutz, Thierry Burnouf, D. Williamson, Kiyoshi Nagai, Gentaro Miyazaki, Jeremy R. H. Tame, Angela M. Gronenborn, Ben F. Luisi, Richard T. Jones and G. Marius Clore and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Daniel Shih

42 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Shih United States 21 728 649 598 289 269 42 1.5k
George F. Atweh United States 29 521 0.7× 1.4k 2.1× 1.1k 1.8× 273 0.9× 269 1.0× 59 2.6k
Marjorie Brand Canada 33 186 0.3× 3.1k 4.7× 266 0.4× 81 0.3× 228 0.8× 65 3.5k
Asya V. Grinberg United States 19 128 0.2× 1.1k 1.7× 464 0.8× 59 0.2× 286 1.1× 38 1.8k
Leszek Kotula United States 25 393 0.5× 851 1.3× 89 0.1× 25 0.1× 605 2.2× 52 1.5k
Ilse Oberbäumer Germany 18 225 0.3× 624 1.0× 55 0.1× 45 0.2× 81 0.3× 27 1.3k
Marie Trudel Canada 30 161 0.2× 1.7k 2.7× 582 1.0× 195 0.7× 371 1.4× 71 2.5k
Andrew Chi United States 17 154 0.2× 329 0.5× 210 0.4× 55 0.2× 23 0.1× 34 871
Fatih Kocabaş Türkiye 16 142 0.2× 1.4k 2.1× 205 0.3× 37 0.1× 154 0.6× 55 2.1k
J K Anderson United States 13 158 0.2× 949 1.5× 60 0.1× 30 0.1× 123 0.5× 21 1.4k
W H Tung United States 11 227 0.3× 631 1.0× 114 0.2× 54 0.2× 262 1.0× 12 1.3k

Countries citing papers authored by Daniel Shih

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Shih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Shih

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

All Works

20 of 20 papers shown
1.
Ho, Cheng‐Maw, Yahui Chen, Hui‐Ling Chen, et al.. (2019). Therapeutic efficacy of adipose-derived stromal vascular fraction cells is associated with CD34 positivity in acute-on-chronic liver failure. Cytotherapy. 21(5). 561–565. 1 indexed citations
2.
Shih, Daniel & Thierry Burnouf. (2014). Preparation, quality criteria, and properties of human blood platelet lysate supplements for ex vivo stem cell expansion. New Biotechnology. 32(1). 199–211. 140 indexed citations
3.
Ho, Chih‐Ming, et al.. (2012). Isolation and characterization of stromal progenitor cells from ascites of patients with epithelial ovarian adenocarcinoma. Journal of Biomedical Science. 19(1). 23–23. 47 indexed citations
5.
6.
Yokoyama, Takeshi, Khoon Tee Chong, Gentaro Miyazaki, et al.. (2004). Novel Mechanisms of pH Sensitivity in Tuna Hemoglobin. Journal of Biological Chemistry. 279(27). 28632–28640. 52 indexed citations
7.
Bonaventura, Joseph, et al.. (1999). Altered Ligand Rebinding Kinetics Due to Distal-side Effects in Hemoglobin Chico (Lysβ66(E10) → Thr). Journal of Biological Chemistry. 274(13). 8686–8693. 6 indexed citations
8.
Lappin, Terence R.J., Virgil F. Fairbanks, Richard T. Jones, et al.. (1998). Hemoglobin Old Dominion/Burton-upon-Trent, beta 143 (H21) His-->Tyr, codon 143 CAC-->TAC--a variant with altered oxygen affinity that compromises measurement of glycated hemoglobin in diabetes mellitus: structure, function, and DNA sequence.. PubMed. 73(4). 321–8. 15 indexed citations
9.
Jones, Richard T., Daniel Shih, Thomas S. Fujita, et al.. (1996). A Doubly Cross-linked Human Hemoglobin. Journal of Biological Chemistry. 271(2). 675–680. 23 indexed citations
10.
Stabler, Sally P., et al.. (1994). Hemoglobin Denver [α2β241 (C7) Phe→Ser]: A Low-O2-Affinity Variant Associated With Chronic Cyanosis and Anemia. Mayo Clinic Proceedings. 69(3). 237–243. 11 indexed citations
11.
Perutz, M. F., Daniel Shih, & D. Williamson. (1994). The Chloride Effect in Human Haemoglobin. Journal of Molecular Biology. 239(4). 555–560. 111 indexed citations
12.
Komiyama, Noboru H., Jeremy R. H. Tame, Josée Pagnier, et al.. (1994). [22] Production of human hemoglobin in Escherichia coli using cleavable fusion protein expression vector. Methods in enzymology on CD-ROM/Methods in enzymology. 231. 347–364. 15 indexed citations
14.
Fermi, G., M. F. Perutz, D. Williamson, Penelope E. Stein, & Daniel Shih. (1992). Structure-function relationships in the low-affinity mutant haemoglobin aalborg (Gly74 (E18)β → Arg). Journal of Molecular Biology. 226(3). 883–888. 7 indexed citations
15.
Imai, Kiyohiro, Kenzo Fushitani, Gentaro Miyazaki, et al.. (1991). Site-directed mutagenesis in haemoglobin. Journal of Molecular Biology. 218(4). 769–778. 39 indexed citations
16.
Tame, Jeremy R. H., et al.. (1990). Effect of the distal residues on the vibrational modes of the iron-carbon monoxide bond in hemoglobin studied by protein engineering. Biochemistry. 29(23). 5562–5566. 18 indexed citations
17.
Moo-Penn, Winston F., Danny L. Jue, Mary Johnson, et al.. (1988). Hemoglobin Brockton [.beta.138 (H16) Ala .fwdarw. Pro]: an unstable variant near the C-terminus of the .beta.-subunits with normal oxygen-binding properties. Biochemistry. 27(20). 7614–7619. 17 indexed citations
18.
Kavanaugh, Michael P., Daniel Shih, & Richard T. Jones. (1988). Affinity labeling of hemoglobin with 4,4'-diisothiocyanostilbene-2,2'-disulfonate: covalent cross-linking in the 2,3-diphosphoglycerate binding site. Biochemistry. 27(5). 1804–1808. 29 indexed citations
19.
Kavanaugh, Michael P., Daniel Shih, & Richard T. Jones. (1987). Modification of Hemoglobin with Site-Directed Bifunctional Reagents. Acta Haematologica. 78(2-3). 99–104. 3 indexed citations
20.
Nagai, Kiyoshi, Ben F. Luisi, Daniel Shih, et al.. (1987). Distal residues in the oxygen binding site of haemoglobin studied by protein engineering. Nature. 329(6142). 858–860. 140 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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