Alphan Altınok

1.2k total citations
25 papers, 847 citations indexed

About

Alphan Altınok is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Biophysics. According to data from OpenAlex, Alphan Altınok has authored 25 papers receiving a total of 847 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 7 papers in Computer Vision and Pattern Recognition and 6 papers in Biophysics. Recurrent topics in Alphan Altınok's work include Cell Image Analysis Techniques (6 papers), Planetary Science and Exploration (4 papers) and Medical Image Segmentation Techniques (3 papers). Alphan Altınok is often cited by papers focused on Cell Image Analysis Techniques (6 papers), Planetary Science and Exploration (4 papers) and Medical Image Segmentation Techniques (3 papers). Alphan Altınok collaborates with scholars based in United States, United Kingdom and France. Alphan Altınok's co-authors include Michael B. Elowitz, Eric Mjolsness, Peter S. Swain, James Locke, Nitzan Rosenfeld, Jonathan W. Young, M. Azim Surani, Jamie A. Hackett, Zakary S. Singer and Julia Tischler and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Molecular Cell.

In The Last Decade

Alphan Altınok

22 papers receiving 838 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alphan Altınok United States 13 505 182 116 91 84 25 847
Emmanuel Faure France 10 386 0.8× 216 1.2× 60 0.5× 130 1.4× 62 0.7× 21 749
Ming‐Tang Chen Taiwan 13 546 1.1× 52 0.3× 116 1.0× 147 1.6× 37 0.4× 78 999
Brian Cleary United States 11 973 1.9× 117 0.6× 118 1.0× 50 0.5× 52 0.6× 17 1.2k
Thomas J. Herbert United States 11 106 0.2× 53 0.3× 80 0.7× 84 0.9× 109 1.3× 37 683
Yuriy Mileyko United States 12 251 0.5× 114 0.6× 218 1.9× 33 0.4× 764 9.1× 17 1.4k
Geoffrey Schiebinger Canada 12 679 1.3× 141 0.8× 38 0.3× 70 0.8× 201 2.4× 22 1.0k
Philip J. Harrison Sweden 15 119 0.2× 155 0.9× 36 0.3× 51 0.6× 52 0.6× 24 764
Joke Blom Netherlands 14 536 1.1× 35 0.2× 123 1.1× 31 0.3× 28 0.3× 49 977
Alain Trubuil France 11 299 0.6× 63 0.3× 91 0.8× 33 0.4× 452 5.4× 29 1.1k
Ekaterina Myasnikova Russia 15 1.2k 2.4× 121 0.7× 250 2.2× 24 0.3× 212 2.5× 49 1.4k

Countries citing papers authored by Alphan Altınok

Since Specialization
Citations

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

Fields of papers citing papers by Alphan Altınok

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alphan Altınok

This figure shows the co-authorship network connecting the top 25 collaborators of Alphan Altınok. A scholar is included among the top collaborators of Alphan Altınok 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 Alphan Altınok. Alphan Altınok 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.
Pearson, Kyle A., et al.. (2024). Mapping “Brain Terrain” Regions on Mars Using Deep Learning. The Planetary Science Journal. 5(7). 167–167.
2.
Pearson, Kyle A., et al.. (2023). Mapping "Brain Coral" Regions on Mars Using Deep Learning. 4943–4945.
3.
Crichton, Daniel, L. Cinquini, A. Mahabal, et al.. (2022). From space to biomedicine: Enabling biomarker data science in the cloud. Cancer Biomarkers. 33(4). 479–488. 2 indexed citations
4.
Gibson, Peter B., William E. Chapman, Alphan Altınok, et al.. (2021). Training machine learning models on climate model output yields skillful interpretable seasonal precipitation forecasts. Communications Earth & Environment. 2(1). 93 indexed citations
5.
Blanchet, Gwendoline, et al.. (2021). The Sco-Flooddam Project: New Observing Strategies for Flood Detection, Alert and Rapid Mapping. 1464–1467. 10 indexed citations
6.
Crichton, Daniel, Alphan Altınok, Christopher I. Amos, et al.. (2020). Cancer Biomarkers and Big Data: A Planetary Science Approach. Cancer Cell. 38(6). 757–760. 15 indexed citations
7.
Li, Ting, An Yan, Neha Bhatia, et al.. (2019). Calcium signals are necessary to establish auxin transporter polarity in a plant stem cell niche. Nature Communications. 10(1). 726–726. 59 indexed citations
8.
Altınok, Alphan, et al.. (2018). Modeling Key Predictors of Airport Runway Configurations Using Learning Algorithms. 2018 Aviation Technology, Integration, and Operations Conference. 2 indexed citations
9.
Bue, Brian, et al.. (2017). Automated Content Detection for Cassini Images. 1986. 7048. 1 indexed citations
10.
Thompson, David R., Alphan Altınok, B. Bornstein, et al.. (2015). Onboard machine learning classification of images by a cubesat in Earth orbit. 1(4). 38–40. 7 indexed citations
11.
Altınok, Alphan, B. Bornstein, Tara Estlin, et al.. (2014). Automatic Image Analysis for Adaptive Instrument Targeting: Applications to MSL and Mars 2020. Lunar and Planetary Science Conference. 2871. 1 indexed citations
12.
Thompson, David R., et al.. (2014). Smarter Instruments, Smarter Archives: Machine Learning for Tactical Science. 2014 AGU Fall Meeting. 2014.
13.
Singer, Zakary S., John Yong, Julia Tischler, et al.. (2014). Dynamic Heterogeneity and DNA Methylation in Embryonic Stem Cells. Molecular Cell. 55(2). 319–331. 214 indexed citations
14.
Cunha, Alexandre, Paul T. Tarr, Adrienne Roeder, et al.. (2012). Computational Analysis of Live Cell Images of the Arabidopsis thaliana Plant. Methods in cell biology. 110. 285–323. 14 indexed citations
15.
Trisnadi, Nathanie, Alphan Altınok, Angelike Stathopoulos, & Gregory T. Reeves. (2012). Image analysis and empirical modeling of gene and protein expression. Methods. 62(1). 68–78. 14 indexed citations
16.
Kiris, Erkan, Donovan Ventimiglia, Mehmet Emre Sargin, et al.. (2011). Combinatorial Tau Pseudophosphorylation. Journal of Biological Chemistry. 286(16). 14257–14270. 31 indexed citations
17.
Young, Jonathan W., James Locke, Alphan Altınok, et al.. (2011). Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy. Nature Protocols. 7(1). 80–88. 268 indexed citations
18.
Sargin, Mehmet Emre, Alphan Altınok, B.S. Manjunath, & Kenneth Rose. (2010). Variable Length Open Contour Tracking Using a Deformable Trellis. IEEE Transactions on Image Processing. 20(4). 1023–1035. 12 indexed citations
19.
Sargin, Mehmet Emre, Alphan Altınok, Kenneth Rose, & B. S. Manjunath. (2008). Deformable trellis: open contour tracking in bio-image sequences. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. 2. 561–564. 9 indexed citations
20.
Sargin, Mehmet Emre, Alphan Altınok, Kenneth Rose, & B.S. Manjunath. (2007). Tracing Curvilinear Structures in Live Cell Images. VI – 285. 19 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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