Leena Salmela

3.2k total citations · 1 hit paper
35 papers, 1.1k citations indexed

About

Leena Salmela is a scholar working on Molecular Biology, Artificial Intelligence and Plant Science. According to data from OpenAlex, Leena Salmela has authored 35 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 11 papers in Artificial Intelligence and 8 papers in Plant Science. Recurrent topics in Leena Salmela's work include Genomics and Phylogenetic Studies (24 papers), RNA and protein synthesis mechanisms (10 papers) and Algorithms and Data Compression (10 papers). Leena Salmela is often cited by papers focused on Genomics and Phylogenetic Studies (24 papers), RNA and protein synthesis mechanisms (10 papers) and Algorithms and Data Compression (10 papers). Leena Salmela collaborates with scholars based in Finland, United States and France. Leena Salmela's co-authors include Éric Rivals, Jan Schröder, Jorma Tarhio, Esko Ukkonen, Veli Mäkinen, Simon J. Puglisi, Niko Välimäki, Alexandru I. Tomescu, Christina Boucher and Hannu Peltola and has published in prestigious journals such as Bioinformatics, PLoS ONE and Molecular Ecology.

In The Last Decade

Leena Salmela

33 papers receiving 1.0k citations

Hit Papers

align trajectories sort by overperformance

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.

LoRDEC: accurate and efficient long read error correction

2014 520 citations Leena Salmela, Éric Rivals Bioinformatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Leena Salmela Finland	12	751	280	200	136	127	35	1.1k
Sanchit Misra United States	14	423 0.6×	161 0.6×	246 1.2×	163 1.2×	87 0.7×	41	1.0k
Ilya Shlyakhter United States	14	689 0.9×	291 1.0×	228 1.1×	291 2.1×	174 1.4×	19	1.5k
Guillaume Rizk France	10	572 0.8×	177 0.6×	246 1.2×	116 0.9×	102 0.8×	12	804
Marie-France Sagot France	18	1.0k 1.4×	209 0.7×	206 1.0×	176 1.3×	147 1.2×	57	1.4k
Éric Rivals France	23	1.8k 2.4×	531 1.9×	394 2.0×	362 2.7×	232 1.8×	78	2.3k
Marie‐France Sagot France	21	712 0.9×	324 1.2×	132 0.7×	221 1.6×	78 0.6×	53	1.4k
Alberto Policriti Italy	18	600 0.8×	406 1.4×	422 2.1×	91 0.7×	88 0.7×	112	1.5k
Lucas B. Carey Spain	19	974 1.3×	112 0.4×	89 0.4×	219 1.6×	37 0.3×	33	1.3k
Dominique Lavenier France	17	605 0.8×	133 0.5×	285 1.4×	88 0.6×	120 0.9×	66	1.1k
Gregory Butler Canada	16	409 0.5×	187 0.7×	276 1.4×	84 0.6×	85 0.7×	68	1.2k

Countries citing papers authored by Leena Salmela

Since Specialization

Citations

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

Fields of papers citing papers by Leena Salmela

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leena Salmela

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

All Works

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20 of 20 papers shown

1.

Salmela, Leena, et al.. (2023). SAKE: Strobemer-assisted k-mer extraction. PLoS ONE. 18(11). e0294415–e0294415.

2.

Ma, Jun, Manuel Cáceres, Leena Salmela, Veli Mäkinen, & Alexandru I. Tomescu. (2023). Chaining for accurate alignment of erroneous long reads to acyclic variation graphs. Bioinformatics. 39(8). 8 indexed citations

3.

Salmela, Leena, et al.. (2021). Extraction of Long k-mers Using Spaced Seeds. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(6). 3444–3455. 4 indexed citations

4.

Rossi, Massimiliano, et al.. (2021). Fast and efficient Rmap assembly using the Bi-labelled de Bruijn graph. Algorithms for Molecular Biology. 16(1). 6–6. 1 indexed citations

5.

Kuhnle, Alan, et al.. (2020). Succinct dynamic de Bruijn graphs. Bioinformatics. 37(14). 1946–1952. 4 indexed citations

6.

Salmela, Leena, et al.. (2020). Optical map guided genome assembly. BMC Bioinformatics. 21(1). 285–285. 9 indexed citations

7.

Ladra, Susana, et al.. (2020). Inference of viral quasispecies with a paired de Bruijn graph. Bioinformatics. 37(4). 473–481. 6 indexed citations

8.

Salmela, Leena, et al.. (2019). Safe and Complete Algorithms for Dynamic Programming Problems, with an Application to RNA Folding. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 1 indexed citations

9.

Salmela, Leena, et al.. (2019). Fast and accurate correction of optical mapping data via spaced seeds. Bioinformatics. 36(3). 682–689. 2 indexed citations

10.

Rastas, Pasi, et al.. (2019). Kermit: linkage map guided long read assembly. Algorithms for Molecular Biology. 14(1). 8–8. 4 indexed citations

11.

Salmela, Leena & Alexandru I. Tomescu. (2018). Safely Filling Gaps with Partial Solutions Common to All Solutions. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 16(2). 617–626. 1 indexed citations

12.

Muggli, Martin D., et al.. (2018). Error correcting optical mapping data. GigaScience. 7(6). 11 indexed citations

13.

Rastas, Pasi, et al.. (2018). Kermit: Guided Long Read Assembly using Coloured Overlap Graphs. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 1 indexed citations

14.

Salmela, Leena, et al.. (2017). Variant genotyping with gap filling. PLoS ONE. 12(9). e0184608–e0184608. 2 indexed citations

15.

Bras, Yvan Le, Olivier Collin, Vincent Lacroix, et al.. (2016). Colib'read on galaxy: a tools suite dedicated to biological information extraction from raw NGS reads. GigaScience. 5(1). 9–9. 3 indexed citations

16.

Salmela, Leena & Éric Rivals. (2014). LoRDEC: accurate and efficient long read error correction. Bioinformatics. 30(24). 3506–3514. 520 indexed citations breakdown →

17.

Claude, Francisco, Gonzalo Navarro, Hannu Peltola, Leena Salmela, & Jorma Tarhio. (2010). String matching with alphabet sampling. Journal of Discrete Algorithms. 11. 37–50. 13 indexed citations

18.

Salmela, Leena, et al.. (2009). Towards automated management of compiler assignments. 243–249. 1 indexed citations

19.

Salmela, Leena & Jorma Tarhio. (2008). Fast parameterized matching with q-grams. Journal of Discrete Algorithms. 6(3). 408–419. 11 indexed citations

20.

Salmela, Leena & Jorma Tarhio. (2004). ACE: Automated Compiler Exercises. 4 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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