Raluca Uricaru

578 total citations
13 papers, 281 citations indexed

About

Raluca Uricaru is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Raluca Uricaru has authored 13 papers receiving a total of 281 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 3 papers in Artificial Intelligence and 3 papers in Genetics. Recurrent topics in Raluca Uricaru's work include Genomics and Phylogenetic Studies (10 papers), RNA and protein synthesis mechanisms (4 papers) and Gene expression and cancer classification (3 papers). Raluca Uricaru is often cited by papers focused on Genomics and Phylogenetic Studies (10 papers), RNA and protein synthesis mechanisms (4 papers) and Gene expression and cancer classification (3 papers). Raluca Uricaru collaborates with scholars based in France, Austria and Canada. Raluca Uricaru's co-authors include Rayan Chikhi, Vincent Lacroix, Pierre Peterlongo, Claire Lemaitre, Guillaume Rizk, Patricia Thébault, Élodie Darbo, Janice Kielbassa, Pavlos Antoniou and Marie-France Sagot and has published in prestigious journals such as Nucleic Acids Research, BMC Bioinformatics and Briefings in Bioinformatics.

In The Last Decade

Raluca Uricaru

13 papers receiving 276 citations

Peers

Countries citing papers authored by Raluca Uricaru

Since Specialization

Citations

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

Fields of papers citing papers by Raluca Uricaru

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raluca Uricaru

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

All Works

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13 of 13 papers shown

#	Work	Indexed citations
1	Optimizing hybrid ensemble feature selection strategies for transcriptomic biomarker discovery in complex diseases 2024 ·NAR Genomics and Bioinformatics ·(unknown), Mickaël Leclercq, Patricia Thébault, Arnaud Droit, Raluca Uricaru	3
2	Consensus clustering applied to multi-omics disease subtyping 2021 ·BMC Bioinformatics ·(unknown), Élodie Darbo, Patricia Thébault, Raluca Uricaru	53
3	Colib'read on galaxy: a tools suite dedicated to biological information extraction from raw NGS reads 2016 ·GigaScience ·Yvan Le Bras, Olivier Collin, (unknown), Vincent Lacroix, Éric Rivals, Claire Lemaitre, Vincent Mièle, (unknown), Camille Marchet, (unknown), Amal Zine El Aabidine, Leena Salmela, (unknown), (unknown), Raluca Uricaru, Pierre Peterlongo	3
4	MICADo – Looking for Mutations in Targeted PacBio Cancer Data: An Alignment-Free Method 2016 ·Frontiers in Genetics ·Justine Rudewicz, (unknown), Raluca Uricaru, Hervé Bonnefoi, Richard Iggo, Jonas Bergh, Macha Nikolski	3
5	YOC, A new strategy for pairwise alignment of collinear genomes 2015 ·BMC Bioinformatics ·Raluca Uricaru, Célia Michotey, Hélène Chiapello, Éric Rivals	5
6	Reference-free compression of high throughput sequencing data with a probabilistic de Bruijn graph 2015 ·BMC Bioinformatics ·Gaëtan Benoit, Claire Lemaitre, Dominique Lavenier, Erwan Drézen, (unknown), Raluca Uricaru, Guillaume Rizk	56
7	Reference-free detection of isolated SNPs 2014 ·Nucleic Acids Research ·Raluca Uricaru, Guillaume Rizk, Vincent Lacroix, Elsa Quillery, Olivier Plantard, Rayan Chikhi, Claire Lemaitre, Pierre Peterlongo	62
8	Advantages of mixing bioinformatics and visualization approaches for analyzing sRNA-mediated regulatory bacterial networks 2014 ·Briefings in Bioinformatics ·Patricia Thébault, Romain Bourqui, (unknown), Christine Gaspin, Pascal Sirand‐Pugnet, Raluca Uricaru, (unknown)	8
9	KIS SPLICE: de-novo calling alternative splicing events from RNA-seq data 2012 ·BMC Bioinformatics ·(unknown), Janice Kielbassa, Rayan Chikhi, Raluca Uricaru, Pavlos Antoniou, Marie-France Sagot, Pierre Peterlongo, Vincent Lacroix	76
10	An alternative approach to multiple genome comparison 2011 ·Nucleic Acids Research ·(unknown), Raluca Uricaru, Éric Rivals	5
11	Novel Definition and Algorithm for Chaining Fragments with Proportional Overlaps 2011 ·Journal of Computational Biology ·Raluca Uricaru, (unknown), Éric Rivals	3
12	A new type of Hidden Markov Models to predict complex domain architecture in protein sequences 2007 ·HAL (Le Centre pour la Communication Scientifique Directe) ·Raluca Uricaru, Laurent Bréhélin, Éric Rivals	2
13	A new type of Hidden Markov Models to predict complex motif organization in protein sequences 2006 ·HAL (Le Centre pour la Communication Scientifique Directe) ·Raluca Uricaru, Laurent Bréhélin, Éric Rivals	2

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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