Christina M. Birch

1.2k total citations · 1 hit paper
7 papers, 882 citations indexed

About

Christina M. Birch is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Physiology. According to data from OpenAlex, Christina M. Birch has authored 7 papers receiving a total of 882 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Physiology. Recurrent topics in Christina M. Birch's work include Microfluidic and Bio-sensing Technologies (2 papers), Mathematical Biology Tumor Growth (2 papers) and Digital Imaging for Blood Diseases (2 papers). Christina M. Birch is often cited by papers focused on Microfluidic and Bio-sensing Technologies (2 papers), Mathematical Biology Tumor Growth (2 papers) and Digital Imaging for Blood Diseases (2 papers). Christina M. Birch collaborates with scholars based in United States and Singapore. Christina M. Birch's co-authors include Aasia Saleemuddin, Alexander Miron, Judy E. Garber, Ronny Drapkin, Fabíola Medeiros, Haiwei Mou, Thomas S. Deisboeck, Jongyoon Han, Jacquin C. Niles and Han Wei Hou and has published in prestigious journals such as Nature, Bioinformatics and Molecular and Cellular Biology.

In The Last Decade

Christina M. Birch

7 papers receiving 869 citations

Hit Papers

A candidate precursor to serous carcinoma that originates... 2006 2026 2012 2019 2006 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christina M. Birch United States 6 581 309 220 159 141 7 882
Eliane T. Taube Germany 15 316 0.5× 175 0.6× 162 0.7× 70 0.4× 165 1.2× 53 637
Hideki Kuroda Japan 11 272 0.5× 208 0.7× 93 0.4× 42 0.3× 88 0.6× 30 594
Megan I. Samuelson United States 13 123 0.2× 169 0.5× 154 0.7× 50 0.3× 98 0.7× 29 495
Rosalía I. Cordo Russo Argentina 14 138 0.2× 432 1.4× 168 0.8× 154 1.0× 203 1.4× 27 1.1k
Gaia Giannone Italy 14 204 0.4× 262 0.8× 103 0.5× 169 1.1× 341 2.4× 32 740
Olivia L. Tan Australia 9 177 0.3× 141 0.5× 42 0.2× 58 0.4× 163 1.2× 15 493
Vanessa Singleton United Kingdom 7 105 0.2× 300 1.0× 39 0.2× 114 0.7× 92 0.7× 8 625
Hervy E. Averette United States 13 113 0.2× 118 0.4× 95 0.4× 33 0.2× 140 1.0× 18 377
Kjell Schedvins Sweden 18 109 0.2× 344 1.1× 55 0.3× 92 0.6× 435 3.1× 21 1.3k
Takuhei Yokoyama Japan 11 141 0.2× 174 0.6× 107 0.5× 63 0.4× 117 0.8× 17 399

Countries citing papers authored by Christina M. Birch

Since Specialization
Citations

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

Fields of papers citing papers by Christina M. Birch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christina M. Birch. 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 Christina M. Birch. The network helps show where Christina M. Birch may publish in the future.

Co-authorship network of co-authors of Christina M. Birch

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

All Works

7 of 7 papers shown
1.
Birch, Christina M., Han Wei Hou, Jongyoon Han, & Jacquin C. Niles. (2015). Identification of malaria parasite-infected red blood cell surface aptamers by inertial microfluidic SELEX (I-SELEX). Nature. 2 indexed citations
2.
Birch, Christina M., Han Wei Hou, Jongyoon Han, & Jacquin C. Niles. (2015). Identification of malaria parasite-infected red blood cell surface aptamers by inertial microfluidic SELEX (I-SELEX). Scientific Reports. 5(1). 11347–11347. 57 indexed citations
3.
Sun, Zheng, Tongde Wu, Fei Zhao, et al.. (2011). KPNA6 (Importin α7)-Mediated Nuclear Import of Keap1 Represses the Nrf2-Dependent Antioxidant Response. Molecular and Cellular Biology. 31(9). 1800–1811. 73 indexed citations
4.
Wang, Zhihui, Christina M. Birch, Jonathan Sagotsky, & Thomas S. Deisboeck. (2009). Cross-scale, cross-pathway evaluation using an agent-based non-small cell lung cancer model. Bioinformatics. 25(18). 2389–2396. 56 indexed citations
5.
Wang, Zhihui, Christina M. Birch, & Thomas S. Deisboeck. (2008). Cross-scale sensitivity analysis of a non-small cell lung cancer model: Linking molecular signaling properties to cellular behavior. Biosystems. 92(3). 249–258. 25 indexed citations
6.
Miron, Alexander, Ronny Drapkin, Fabíola Medeiros, et al.. (2007). A candidate precursor to serous carcinoma that originates in the distal fallopian tube (J Pathol 2007; 211: 26–35). The Journal of Pathology. 213(1). 116–116. 19 indexed citations
7.
Miron, Alexander, Ronny Drapkin, Fabíola Medeiros, et al.. (2006). A candidate precursor to serous carcinoma that originates in the distal fallopian tube. The Journal of Pathology. 211(1). 26–35. 650 indexed citations breakdown →

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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