Ney Lemke

1.9k total citations
62 papers, 1.3k citations indexed

About

Ney Lemke is a scholar working on Molecular Biology, Condensed Matter Physics and Statistical and Nonlinear Physics. According to data from OpenAlex, Ney Lemke has authored 62 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 9 papers in Condensed Matter Physics and 8 papers in Statistical and Nonlinear Physics. Recurrent topics in Ney Lemke's work include Bioinformatics and Genomic Networks (18 papers), Theoretical and Computational Physics (9 papers) and Microbial Metabolic Engineering and Bioproduction (8 papers). Ney Lemke is often cited by papers focused on Bioinformatics and Genomic Networks (18 papers), Theoretical and Computational Physics (9 papers) and Microbial Metabolic Engineering and Bioproduction (8 papers). Ney Lemke collaborates with scholars based in Brazil, France and United States. Ney Lemke's co-authors include Márcio Luís Acencio, Luiz A. Bovolenta, José C. M. Mombach, Xue Zhang, Günther J.L. Gerhardt, Suzana Veiga Schönwald, I. A. Campbell, Danillo Pinhal, B. E. J. Bodmann and Pedro G. Nachtigall and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Ney Lemke

60 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ney Lemke Brazil 19 877 219 148 123 122 62 1.3k
Fergal Casey United States 15 926 1.1× 139 0.6× 63 0.4× 78 0.6× 211 1.7× 35 1.5k
Denis Dupuy France 16 2.2k 2.5× 264 1.2× 118 0.8× 32 0.3× 267 2.2× 29 2.8k
Nicolas Bertin United States 14 2.6k 2.9× 357 1.6× 185 1.3× 29 0.2× 247 2.0× 23 3.1k
Michael Livstone United States 9 2.2k 2.5× 380 1.7× 168 1.1× 19 0.2× 295 2.4× 10 2.8k
Andrzej Kudlicki United States 17 1.2k 1.3× 126 0.6× 141 1.0× 15 0.1× 95 0.8× 49 1.6k
Francisco S. Domingues Germany 26 2.1k 2.4× 339 1.5× 149 1.0× 24 0.2× 152 1.2× 75 3.1k
Lan V. Zhang United States 7 1.7k 1.9× 285 1.3× 68 0.5× 14 0.1× 169 1.4× 7 1.9k
Timothy R. Lezon United States 13 1.3k 1.5× 203 0.9× 28 0.2× 47 0.4× 93 0.8× 24 1.6k
David Juan Spain 26 2.3k 2.6× 146 0.7× 528 3.6× 62 0.5× 426 3.5× 54 3.0k
Yuvalal Liron Israel 12 1.5k 1.8× 74 0.3× 109 0.7× 26 0.2× 171 1.4× 16 1.9k

Countries citing papers authored by Ney Lemke

Since Specialization
Citations

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

Fields of papers citing papers by Ney Lemke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ney Lemke

This figure shows the co-authorship network connecting the top 25 collaborators of Ney Lemke. A scholar is included among the top collaborators of Ney Lemke 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 Ney Lemke. Ney Lemke 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.
Nachtigall, Pedro G., Luiz A. Bovolenta, James G. Patton, et al.. (2021). A comparative analysis of heart microRNAs in vertebrates brings novel insights into the evolution of genetic regulatory networks. BMC Genomics. 22(1). 153–153. 2 indexed citations
2.
Bovolenta, Luiz A., Danillo Pinhal, Márcio Luís Acencio, et al.. (2020). miRTil: An Extensive Repository for Nile Tilapia microRNA Next Generation Sequencing Data. Cells. 9(8). 1752–1752. 3 indexed citations
3.
Bovolenta, Luiz A., et al.. (2019). Understanding the Modus Operandi of MicroRNA Regulatory Clusters. Cells. 8(9). 1103–1103. 13 indexed citations
4.
Pinhal, Danillo, Luiz A. Bovolenta, Simon Moxon, et al.. (2018). Genome-wide microRNA screening in Nile tilapia reveals pervasive isomiRs’ transcription, sex-biased arm switching and increasing complexity of expression throughout development. Scientific Reports. 8(1). 8248–8248. 24 indexed citations
5.
Borges, Rafael J., Ney Lemke, & Marcos R.M. Fontes. (2017). PLA2-like proteins myotoxic mechanism: a dynamic model description. Scientific Reports. 7(1). 15514–15514. 32 indexed citations
6.
Bovolenta, Luiz A., et al.. (2017). Combining Results from Distinct MicroRNA Target Prediction Tools Enhances the Performance of Analyses. Frontiers in Genetics. 8. 59–59. 73 indexed citations
7.
Zhang, Xue, Márcio Luís Acencio, & Ney Lemke. (2016). Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive Review. Frontiers in Physiology. 7. 617–617. 69 indexed citations
8.
Zhang, Xue, Márcio Luís Acencio, & Ney Lemke. (2016). Corrigendum: Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive Review. Frontiers in Physiology. 7. 8 indexed citations
9.
Lemke, Ney, et al.. (2016). Gene polymorphisms as a predictor of body weight loss after Roux-en-Y gastric bypass surgery among obese women. Obesity Research & Clinical Practice. 10(6). 724–727. 17 indexed citations
10.
Gerhardt, Günther J.L., et al.. (2016). Synchronization and Propagation of Global Sleep Spindles. PLoS ONE. 11(3). e0151369–e0151369. 17 indexed citations
11.
Folador, Edson Luiz, Syed Shah Hassan, Ney Lemke, et al.. (2014). An improved interolog mapping-based computational prediction of protein–protein interactions with increased network coverage. Integrative Biology. 6(11). 1080–1087. 26 indexed citations
12.
Carvalho, Diego Z., et al.. (2014). Loss of sleep spindle frequency deceleration in Obstructive Sleep Apnea. Clinical Neurophysiology. 125(2). 306–312. 51 indexed citations
13.
Acencio, Márcio Luís, et al.. (2013). Cooperative RNA Polymerase Molecules Behavior on a Stochastic Sequence-Dependent Model for Transcription Elongation. PLoS ONE. 8(2). e57328–e57328. 9 indexed citations
14.
Valente, Guilherme Targino, Márcio Luís Acencio, Cesar Martins, & Ney Lemke. (2013). The Development of a Universal In Silico Predictor of Protein-Protein Interactions. PLoS ONE. 8(5). e65587–e65587. 32 indexed citations
15.
16.
Acencio, Márcio Luís & Ney Lemke. (2009). Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information. BMC Bioinformatics. 10(1). 290–290. 147 indexed citations
17.
Sinigaglia, Marialva, et al.. (2008). Cupin: A candidate molecular structure for the Nep1-like protein family. BMC Plant Biology. 8(1). 50–50. 9 indexed citations
18.
Sinigaglia, Marialva, José C. M. Mombach, Sérgio Echeverrigaray, et al.. (2008). Can Nep1-like proteins form oligomers?. Plant Signaling & Behavior. 3(10). 906–907. 2 indexed citations
19.
Lemke, Ney, et al.. (2003). Essentiality and damage in metabolic networks. Bioinformatics. 20(1). 115–119. 62 indexed citations
20.
Almeida, Rita M. C. de, Ney Lemke, & I. A. Campbell. (2000). Stretched exponential relaxation and independent relaxation modes. Brazilian Journal of Physics. 30(4). 1 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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