Leonidas Bleris

2.8k total citations
65 papers, 1.9k citations indexed

About

Leonidas Bleris is a scholar working on Molecular Biology, Control and Systems Engineering and Hardware and Architecture. According to data from OpenAlex, Leonidas Bleris has authored 65 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 14 papers in Control and Systems Engineering and 10 papers in Hardware and Architecture. Recurrent topics in Leonidas Bleris's work include CRISPR and Genetic Engineering (18 papers), Gene Regulatory Network Analysis (15 papers) and Advanced Control Systems Optimization (13 papers). Leonidas Bleris is often cited by papers focused on CRISPR and Genetic Engineering (18 papers), Gene Regulatory Network Analysis (15 papers) and Advanced Control Systems Optimization (13 papers). Leonidas Bleris collaborates with scholars based in United States, China and Switzerland. Leonidas Bleris's co-authors include Yaakov Benenson, Mayuresh V. Kothare, Yi Li, Mark G. Arnold, Rohan Maddamsetti, Sairam Subramanian, Ron Weiss, Zhen Xie, Chance M. Nowak and Richard Moore and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Biotechnology.

In The Last Decade

Leonidas Bleris

65 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Leonidas Bleris United States 22 1.2k 256 229 222 136 65 1.9k
Boyan Yordanov United Kingdom 15 727 0.6× 137 0.5× 126 0.6× 17 0.1× 67 0.5× 26 1.2k
Elisa Franco United States 27 1.9k 1.6× 303 1.2× 386 1.7× 51 0.2× 139 1.0× 118 2.5k
Thomas Schulte Germany 20 379 0.3× 210 0.8× 342 1.5× 81 0.4× 43 0.3× 69 1.6k
Jae Young Lee South Korea 23 1.4k 1.2× 143 0.6× 197 0.9× 207 0.9× 255 1.9× 79 2.2k
Yifan Wang China 25 1.1k 0.9× 97 0.4× 131 0.6× 61 0.3× 110 0.8× 111 2.9k
Diego A. Oyarzún United Kingdom 20 1.2k 1.0× 147 0.6× 217 0.9× 56 0.3× 284 2.1× 66 1.7k
Douglas Densmore United States 30 2.2k 1.8× 29 0.1× 994 4.3× 124 0.6× 459 3.4× 100 3.4k
James Gilbert United Kingdom 27 1.6k 1.3× 43 0.2× 137 0.6× 294 1.3× 380 2.8× 50 2.6k
Xiaonan Yang China 19 412 0.3× 24 0.1× 242 1.1× 64 0.3× 31 0.2× 111 1.1k
Shobhit Gupta United States 15 1.3k 1.1× 111 0.4× 75 0.3× 296 1.3× 221 1.6× 37 2.0k

Countries citing papers authored by Leonidas Bleris

Since Specialization
Citations

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

Fields of papers citing papers by Leonidas Bleris

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leonidas Bleris

This figure shows the co-authorship network connecting the top 25 collaborators of Leonidas Bleris. A scholar is included among the top collaborators of Leonidas Bleris 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 Leonidas Bleris. Leonidas Bleris 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.
Makris, Yiorgos, et al.. (2024). The history, landscape, and outlook of human cell line authentication and security. SLAS DISCOVERY. 29(8). 100194–100194. 1 indexed citations
2.
Li, Yi, David S. Moura, Alexey S. Revenko, et al.. (2024). STAT6-targeting antisense oligonucleotides against solitary fibrous tumor. Molecular Therapy — Nucleic Acids. 35(2). 102154–102154. 6 indexed citations
3.
Li, Yi, et al.. (2024). NeurostimML: a machine learning model for predicting neurostimulation-induced tissue damage. Journal of Neural Engineering. 21(3). 36054–36054. 3 indexed citations
4.
Nowak, Chance M., Jessica J. Kandel, Theodore W. Laetsch, et al.. (2023). Non-viral nitric oxide-based gene therapy improves perfusion and liposomal doxorubicin sonopermeation in neuroblastoma models. Theranostics. 13(10). 3402–3418. 11 indexed citations
5.
Li, Yi, Clark A. Meyer, David S. Moura, et al.. (2023). Reduction of Tumor Growth with RNA-Targeting Treatment of the NAB2–STAT6 Fusion Transcript in Solitary Fibrous Tumor Models. Cancers. 15(12). 3127–3127. 2 indexed citations
6.
Pal, Arindam, Qi Cai, Zhenghong Gao, et al.. (2023). Clinical gene therapy development for the central nervous system: Candidates and challenges for AAVs. Journal of Controlled Release. 357. 511–530. 5 indexed citations
7.
Tsimberidou, Apostolia M., Elena Fountzilas, Leonidas Bleris, & Razelle Kurzrock. (2020). Transcriptomics and solid tumors: The next frontier in precision cancer medicine. Seminars in Cancer Biology. 84. 50–59. 61 indexed citations
8.
Li, Yi, et al.. (2019). Coevolutionary Couplings Unravel PAM-Proximal Constraints of CRISPR-SpCas9. Biophysical Journal. 117(9). 1684–1691. 2 indexed citations
9.
Lee, Hamilton, Candace Benjamin, Chance M. Nowak, et al.. (2018). Regulating the Uptake of Viral Nanoparticles in Macrophage and Cancer Cells via a pH Switch. Molecular Pharmaceutics. 15(8). 2984–2990. 11 indexed citations
10.
Dharmarwardana, Madushani, André F. Martins, Zhuo Chen, et al.. (2018). Nitroxyl Modified Tobacco Mosaic Virus as a Metal-Free High-Relaxivity MRI and EPR Active Superoxide Sensor. Molecular Pharmaceutics. 15(8). 2973–2983. 49 indexed citations
11.
Nowak, Chance M., et al.. (2016). Guide RNA engineering for versatile Cas9 functionality. Nucleic Acids Research. 44(20). gkw908–gkw908. 67 indexed citations
12.
Li, Yi, et al.. (2016). Exploiting the CRISPR/Cas9 PAM Constraint for Single-Nucleotide Resolution Interventions. PLoS ONE. 11(1). e0144970–e0144970. 23 indexed citations
13.
Zhang, Michael Q., et al.. (2015). Reconfigurable hybrid interface for molecular marker diagnostics and in-situ reporting. Biosensors and Bioelectronics. 74. 744–750. 5 indexed citations
14.
Moore, Richard, et al.. (2015). Discriminating direct and indirect connectivities in biological networks. Proceedings of the National Academy of Sciences. 112(41). 12893–12898. 21 indexed citations
15.
Xie, Zhen, et al.. (2013). Transcripts for combined synthetic microRNA and gene delivery. Molecular BioSystems. 9(7). 1919–1925. 8 indexed citations
16.
Bleris, Leonidas, Ion Măndoiu, Russell Schwartz, & Jianxin Wang. (2012). Bioinformatics Research and Applications: 8th International Symposium, ISBRA 2012, Dallas, TX, USA, May 21-23, 2012. Proceedings. Springer eBooks. 1 indexed citations
17.
Li, Yi, et al.. (2012). Transcription activator-like effector hybrids for conditional control and rewiring of chromosomal transgene expression. Scientific Reports. 2(1). 897–897. 58 indexed citations
18.
Bleris, Leonidas, et al.. (2010). Linear Control Theory for Gene Network Modeling. PLoS ONE. 5(9). e12785–e12785. 15 indexed citations
19.
Xie, Zhen, Siyuan Liu, Leonidas Bleris, & Yaakov Benenson. (2010). Logic integration of mRNA signals by an RNAi-based molecular computer. Nucleic Acids Research. 38(8). 2692–2701. 46 indexed citations
20.
Vouzis, Panagiotis D., Leonidas Bleris, Mayuresh V. Kothare, & Mark G. Arnold. (2005). Towards a co-design implementation of a system for model predictive control. 7 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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