Christopher Previti

2.5k total citations
11 papers, 461 citations indexed

About

Christopher Previti is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Christopher Previti has authored 11 papers receiving a total of 461 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Cancer Research and 1 paper in Genetics. Recurrent topics in Christopher Previti's work include Genomics and Chromatin Dynamics (6 papers), RNA modifications and cancer (5 papers) and MicroRNA in disease regulation (4 papers). Christopher Previti is often cited by papers focused on Genomics and Chromatin Dynamics (6 papers), RNA modifications and cancer (5 papers) and MicroRNA in disease regulation (4 papers). Christopher Previti collaborates with scholars based in Germany, Norway and Spain. Christopher Previti's co-authors include Michael Hackenberg, Pedro Carpena, Pedro L. Luque‐Escamilla, José Luis Tejera Oliver, José Martı́nez-Aroza, Boris Lenhard, Igor Zwir, Ana Maria Suzuki, Coral del Val and Altuna Akalin and has published in prestigious journals such as Nature, Nucleic Acids Research and BMC Bioinformatics.

In The Last Decade

Christopher Previti

10 papers receiving 451 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher Previti Germany 7 423 104 56 41 12 11 461
Laura Martínez Gómez Spain 8 275 0.7× 149 1.4× 48 0.9× 36 0.9× 8 0.7× 10 336
Benjamin Kreck Germany 4 275 0.7× 51 0.5× 75 1.3× 41 1.0× 2 0.2× 4 325
Eirikur Hjartarson Iceland 3 159 0.4× 29 0.3× 156 2.8× 42 1.0× 10 0.8× 3 286
Thomas Amort Austria 9 650 1.5× 313 3.0× 34 0.6× 40 1.0× 14 1.2× 11 711
Sofia Kyriazopoulou-Panagiotopoulou United States 3 348 0.8× 44 0.4× 119 2.1× 39 1.0× 7 0.6× 4 394
Jacob M. Tome United States 6 416 1.0× 44 0.4× 52 0.9× 33 0.8× 3 0.3× 7 449
Michael T. Kalmbach United States 6 120 0.3× 29 0.3× 89 1.6× 49 1.2× 11 0.9× 8 226
Hongzhe Guo China 6 162 0.4× 77 0.7× 135 2.4× 30 0.7× 6 0.5× 10 269
Malika Saint India 6 358 0.8× 33 0.3× 22 0.4× 38 0.9× 3 0.3× 6 383
Koustav Pal Italy 5 375 0.9× 132 1.3× 66 1.2× 91 2.2× 3 0.3× 9 407

Countries citing papers authored by Christopher Previti

Since Specialization
Citations

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

Fields of papers citing papers by Christopher Previti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher Previti

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

All Works

11 of 11 papers shown
1.
Blattner-Johnson, Mirjam, Dominik Sturm, Steffen Hirsch, et al.. (2024). HGG-21. DISTRIBUTION AND MUTATIONAL PATTERNS OF TP53 ALTERATIONS ACROSS SUBTYPES OF PEDIATRIC HIGH-GRADE GLIOMAS. Neuro-Oncology. 26(Supplement_4). 0–0.
2.
Worst, Thomas Stefan, Christopher Previti, Katja Nitschke, et al.. (2019). miR-10a-5p and miR-29b-3p as Extracellular Vesicle-Associated Prostate Cancer Detection Markers. Cancers. 12(1). 43–43. 58 indexed citations
3.
Haberle, Vanja, Nan Li, Yavor Hadzhiev, et al.. (2014). Two independent transcription initiation codes overlap on vertebrate core promoters. Nature. 507(7492). 381–385. 133 indexed citations
4.
Winter, Julia, et al.. (2013). Loop-miRs: active microRNAs generated from single-stranded loop regions. Nucleic Acids Research. 41(10). 5503–5512. 35 indexed citations
5.
Winz, Marie‐Luise, et al.. (2013). Next-generation sequencing reveals how RNA catalysts evolve from random space. Nucleic Acids Research. 42(2). 1303–1310. 30 indexed citations
6.
Sheng, Ying & Christopher Previti. (2011). Genomic features and computational identification of human microRNAs under long-range developmental regulation. BMC Genomics. 12(1). 270–270. 5 indexed citations
7.
Hackenberg, Michael, Guillermo Barturen, Pedro Carpena, et al.. (2010). Prediction of CpG-island function: CpG clustering vs. sliding-window methods. BMC Genomics. 11(1). 327–327. 39 indexed citations
8.
Previti, Christopher, Oscar Harari, Igor Zwir, & Coral del Val. (2009). Profile analysis and prediction of tissue-specific CpG island methylation classes. BMC Bioinformatics. 10(1). 116–116. 30 indexed citations
9.
Previti, Christopher, Oscar Harari, Igor Zwir, & Coral del Val. (2007). Novel approaches to the prediction of CpG islands and their methylation status. Summer Computer Simulation Conference. 833–840. 1 indexed citations
10.
Previti, Christopher, Oscar Harari, & Coral del Val. (2007). Mining and Predicting CpG islands. Proceedings of ... IEEE International Conference on Fuzzy Systems. 61. 1–6. 1 indexed citations
11.
Hackenberg, Michael, Christopher Previti, Pedro L. Luque‐Escamilla, et al.. (2006). CpGcluster: a distance-based algorithm for CpG-island detection. BMC Bioinformatics. 7(1). 446–446. 129 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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