Sündüz Keleş

11.4k total citations · 1 hit paper
135 papers, 6.0k citations indexed

About

Sündüz Keleş is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Sündüz Keleş has authored 135 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 111 papers in Molecular Biology, 39 papers in Genetics and 11 papers in Cancer Research. Recurrent topics in Sündüz Keleş's work include Genomics and Chromatin Dynamics (44 papers), Epigenetics and DNA Methylation (28 papers) and Gene expression and cancer classification (25 papers). Sündüz Keleş is often cited by papers focused on Genomics and Chromatin Dynamics (44 papers), Epigenetics and DNA Methylation (28 papers) and Gene expression and cancer classification (25 papers). Sündüz Keleş collaborates with scholars based in United States, Switzerland and Türkiye. Sündüz Keleş's co-authors include Hyonho Chun, Emery H. Bresnick, Dongjun Chung, Mark J. van der Laan, Kun Liang, Pei Fen Kuan, Kirby D. Johnson, Tohru Fujiwara, Daniel S. Greenspan and Sandrine Dudoit and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Sündüz Keleş

130 papers receiving 5.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Sparse Partial Least Squares Regression for Simultaneous Dimension Reduction and Variable Selection

2010 619 citations Sündüz Keleş et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sündüz Keleş United States	41	3.6k	1.1k	477	473	463	135	6.0k
Grier P. Page United States	51	4.3k 1.2×	1.7k 1.6×	426 0.9×	1.2k 2.6×	589 1.3×	185	10.0k
Christina Kendziorski United States	39	5.3k 1.5×	1.1k 1.0×	477 1.0×	904 1.9×	1.1k 2.4×	125	7.9k
Xiangqin Cui United States	35	3.6k 1.0×	952 0.9×	337 0.7×	315 0.7×	439 0.9×	120	5.7k
Francesco Falciani United Kingdom	45	2.6k 0.7×	687 0.6×	935 2.0×	228 0.5×	310 0.7×	116	5.7k
Magnus Åstrand Sweden	11	4.5k 1.2×	819 0.8×	620 1.3×	401 0.8×	1.1k 2.3×	32	7.0k
Todd E. Scheetz United States	41	3.5k 1.0×	1.1k 1.0×	587 1.2×	177 0.4×	248 0.5×	140	5.9k
Kenichi Matsubara Japan	41	3.8k 1.1×	985 0.9×	833 1.7×	1.2k 2.5×	636 1.4×	160	8.0k
Itsik Pe’er United States	35	2.7k 0.7×	3.1k 2.8×	485 1.0×	370 0.8×	394 0.9×	99	6.8k
Zhijin Wu United States	29	4.3k 1.2×	1.0k 0.9×	440 0.9×	235 0.5×	776 1.7×	85	6.3k
Zhaohui Qin United States	44	8.0k 2.2×	1.6k 1.5×	633 1.3×	265 0.6×	1.9k 4.0×	179	10.5k

Countries citing papers authored by Sündüz Keleş

Since Specialization

Citations

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

Fields of papers citing papers by Sündüz Keleş

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sündüz Keleş

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Keleş, Mehmet F., Anuradha Mehta, Shahin Ahmadi, et al.. (2025). FlyVISTA, an integrated machine learning platform for deep phenotyping of sleep in Drosophila. Science Advances. 11(11). eadq8131–eadq8131. 3 indexed citations

Keleş, Sündüz, et al.. (2024). Joint Tensor Modeling of Single Cell 3D Genome and Epigenetic Data with Muscle. Journal of the American Statistical Association. 119(548). 2464–2477. 1 indexed citations

Keleş, Sündüz, et al.. (2023). AdaLiftOver: high-resolution identification of orthologous regulatory elements with Adaptive liftOver. Bioinformatics. 39(4). 2 indexed citations

Lu, Shan, Md. Jashim Uddin, Sündüz Keleş, et al.. (2023). Secondary bile acids function through the vitamin D receptor in myeloid progenitors to promote myelopoiesis. Blood Advances. 7(17). 4970–4982. 5 indexed citations

Lu, Shan & Sündüz Keleş. (2023). Debiased personalized gene coexpression networks for population-scale scRNA-seq data. Genome Research. 33(6). 932–947. 10 indexed citations

Lu, Shan, et al.. (2023). MuDCoD: multi-subject community detection in personalized dynamic gene networks from single-cell RNA sequencing. Bioinformatics. 39(10).

Zheng, Ye, et al.. (2022). scGAD: single-cell gene associating domain scores for exploratory analysis of scHi-C data. Bioinformatics. 38(14). 3642–3644. 4 indexed citations

Lu, Shan, et al.. (2021). MLG: multilayer graph clustering for multi-condition scRNA-seq data. Nucleic Acids Research. 49(22). e127–e127. 2 indexed citations

Wu, Yuchang, Junha Shin, Ye Zheng, et al.. (2021). Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder. PLoS Genetics. 17(2). e1009309–e1009309. 11 indexed citations

10.

Liu, Peng, Alexandra A. Soukup, Emery H. Bresnick, Colin N. Dewey, & Sündüz Keleş. (2020). PRAM: a novel pooling approach for discovering intergenic transcripts from large-scale RNA sequencing experiments. Genome Research. 30(11). 1655–1666. 1 indexed citations

11.

Hewitt, Kyle J., Koichi R. Katsumura, Daniel R. Matson, et al.. (2017). GATA Factor-Regulated Samd14 Enhancer Confers Red Blood Cell Regeneration and Survival in Severe Anemia. Developmental Cell. 42(3). 213–225.e4. 30 indexed citations

12.

Sun, Guannan, Rajini Srinivasan, Camila Lopez‐Anido, et al.. (2014). In Silico Pooling of ChIP-seq Control Experiments. PLoS ONE. 9(11). e109691–e109691. 2 indexed citations

13.

Huebert, Dana J., Pei Fen Kuan, Sündüz Keleş, & Audrey P. Gasch. (2012). Dynamic Changes in Nucleosome Occupancy Are Not Predictive of Gene Expression Dynamics but Are Linked to Transcription and Chromatin Regulators. Molecular and Cellular Biology. 32(9). 1645–1653. 45 indexed citations

14.

Chung, Dongjun & Sündüz Keleş. (2010). Sparse Partial Least Squares Classification for High Dimensional Data. Statistical Applications in Genetics and Molecular Biology. 9(1). Article17–Article17. 151 indexed citations

15.

Bravo, Héctor Corrada, Stephen J. Wright, Kevin H. Eng, Sündüz Keleş, & Grace Wahba. (2009). Estimating Tree-Structured Covariance Matrices via Mixed-Integer Programming. International Conference on Artificial Intelligence and Statistics. 41–48. 2 indexed citations

16.

Kuan, Pei Fen, Dana J. Huebert, Audrey P. Gasch, & Sündüz Keleş. (2009). A Non-Homogeneous Hidden-State Model on First Order Differences for Automatic Detection of Nucleosome Positions. Statistical Applications in Genetics and Molecular Biology. 8(1). Article29–Article29. 18 indexed citations

17.

Opperman, Laura, et al.. (2009). A single C. elegans PUF protein binds RNA in multiple modes. RNA. 15(6). 1090–1099. 37 indexed citations

18.

Wei, Hairong, Pei Fen Kuan, Shulan Tian, et al.. (2008). A study of the relationships between oligonucleotide properties and hybridization signal intensities from NimbleGen microarray datasets. Nucleic Acids Research. 36(9). 2926–2938. 36 indexed citations

19.

Keleş, Sündüz, et al.. (2007). The bone morphogenetic protein 1/Tolloid-like metalloproteinases. Matrix Biology. 26(7). 508–523. 195 indexed citations

20.

Keleş, Sündüz. (2006). Mixture Modeling for Genome‐Wide Localization of Transcription Factors. Biometrics. 63(1). 10–21. 33 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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