Harri Lähdesmäki

12.1k total citations · 1 hit paper
136 papers, 5.3k citations indexed

About

Harri Lähdesmäki is a scholar working on Molecular Biology, Immunology and Artificial Intelligence. According to data from OpenAlex, Harri Lähdesmäki has authored 136 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Molecular Biology, 34 papers in Immunology and 18 papers in Artificial Intelligence. Recurrent topics in Harri Lähdesmäki's work include Gene expression and cancer classification (28 papers), Immune Cell Function and Interaction (19 papers) and T-cell and B-cell Immunology (19 papers). Harri Lähdesmäki is often cited by papers focused on Gene expression and cancer classification (28 papers), Immune Cell Function and Interaction (19 papers) and T-cell and B-cell Immunology (19 papers). Harri Lähdesmäki collaborates with scholars based in Finland, United States and United Kingdom. Harri Lähdesmäki's co-authors include Ilya Shmulevich, Tarmo Äijö, Olli Yli‐Harja, Anjana Rao, Riitta Lahesmaa, Susan Togher, Antti Larjo, Patrick G. Hogan, William A. Pastor and Ageliki Tsagaratou and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Harri Lähdesmäki

131 papers receiving 5.2k 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.

The Transcription Factor NFAT Promotes Exhaustion of Activated CD8 + T Cells

2015 532 citations Tarmo Äijö, Susan Togher et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Harri Lähdesmäki Finland	41	2.9k	1.5k	798	677	632	136	5.3k
Jan Aerts Belgium	21	3.3k 1.2×	1.1k 0.8×	564 0.7×	736 1.1×	893 1.4×	65	5.4k
Florian Buettner Germany	26	3.6k 1.2×	855 0.6×	388 0.5×	697 1.0×	506 0.8×	52	5.3k
Matthew T. Weirauch United States	40	6.0k 2.1×	1.1k 0.7×	553 0.7×	831 1.2×	1.1k 1.7×	136	8.9k
Andrzej Maćkiewicz Poland	41	2.8k 1.0×	1.9k 1.3×	1.9k 2.4×	720 1.1×	484 0.8×	196	6.7k
Vân Anh Huynh‐Thu Belgium	14	3.7k 1.3×	1.2k 0.8×	587 0.7×	745 1.1×	288 0.5×	26	5.2k
Greg Finak United States	23	3.2k 1.1×	1.3k 0.9×	1.2k 1.5×	1.1k 1.6×	316 0.5×	42	5.3k
Smita Krishnaswamy United States	25	2.9k 1.0×	1.6k 1.1×	805 1.0×	540 0.8×	186 0.3×	95	5.4k
Simon Lin United States	27	3.3k 1.1×	643 0.4×	484 0.6×	606 0.9×	698 1.1×	72	5.4k
Alistair G. Rust United Kingdom	34	3.0k 1.0×	791 0.5×	646 0.8×	1.2k 1.8×	364 0.6×	76	4.4k
Raphaël Gottardo United States	40	5.2k 1.8×	2.4k 1.6×	1.4k 1.8×	962 1.4×	808 1.3×	130	8.7k

Countries citing papers authored by Harri Lähdesmäki

Since Specialization

Citations

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

Fields of papers citing papers by Harri Lähdesmäki

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Harri Lähdesmäki

This figure shows the co-authorship network connecting the top 25 collaborators of Harri Lähdesmäki. A scholar is included among the top collaborators of Harri Lähdesmäki 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 Harri Lähdesmäki. Harri Lähdesmäki 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

Kurki, Samu, et al.. (2024). A comparative study of clinical trial and real-world data in patients with diabetic kidney disease. Scientific Reports. 14(1). 1731–1731. 9 indexed citations

Huuhtanen, Jani, Katriina Peltola, Tapio Lönnberg, et al.. (2023). Single-cell characterization of anti–LAG-3 and anti–PD-1 combination treatment in patients with melanoma. Journal of Clinical Investigation. 133(6). 60 indexed citations

Lähdesmäki, Harri, et al.. (2023). LuxHMM: DNA methylation analysis with genome segmentation via hidden Markov model. BMC Bioinformatics. 24(1). 58–58. 3 indexed citations

Huuhtanen, Jani, Shady Adnan Awad, Olli Dufva, et al.. (2023). Single-cell analysis of immune recognition in chronic myeloid leukemia patients following tyrosine kinase inhibitor discontinuation. Leukemia. 38(1). 109–125. 17 indexed citations

Jokinen, Emmi, et al.. (2023). TSignal: a transformer model for signal peptide prediction. Bioinformatics. 39(Supplement_1). i347–i356. 8 indexed citations

Eraslan, Gökçen, et al.. (2022). ChromDMM: a Dirichlet-multinomial mixture model for clustering heterogeneous epigenetic data. Bioinformatics. 38(16). 3863–3870. 2 indexed citations

Laajala, Essi, Mari Vähä-Mäkilä, Mirja Nurmio, et al.. (2022). Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood samples. Epigenetics. 17(12). 1608–1627. 2 indexed citations

Huuhtanen, Jani, Liang Chen, Emmi Jokinen, et al.. (2022). Evolution and modulation of antigen-specific T cell responses in melanoma patients. Nature Communications. 13(1). 5988–5988. 22 indexed citations

Laajala, Essi, Taina Härkönen, Sini Junttila, et al.. (2022). Early DNA methylation changes in children developing beta cell autoimmunity at a young age. Diabetologia. 65(5). 844–860. 12 indexed citations

10.

Huuhtanen, Jani, Oscar Brück, Karita Peltonen, et al.. (2021). Single-Cell Characterization of the Immune and Leukemic Cells Following Anti-TIM3 and Hypomethylating Agent Combination Therapy in Patients with AML or MDS. Blood. 138(Supplement 1). 801–801. 1 indexed citations

11.

Koskinen, Miika, et al.. (2021). Latent Gaussian process with composite likelihoods and numerical quadrature. Aaltodoc (Aalto University). 3718–3726. 1 indexed citations

12.

Lähdesmäki, Harri, et al.. (2020). LuxUS: DNA methylation analysis using generalized linear mixed model with spatial correlation. Bioinformatics. 36(17). 4535–4543. 4 indexed citations

13.

Schmidt, Angelika, Francesco Marabita, Narsis A. Kiani, et al.. (2018). Time-resolved transcriptome and proteome landscape of human regulatory T cell (Treg) differentiation reveals novel regulators of FOXP3. BMC Biology. 16(1). 47–47. 48 indexed citations

14.

Ullah, Ubaid, Subhash Tripathi, Kartiek Kanduri, et al.. (2018). Transcriptional Repressor HIC1 Contributes to Suppressive Function of Human Induced Regulatory T Cells. Cell Reports. 22(8). 2094–2106. 49 indexed citations

15.

Heinonen, Markus, et al.. (2018). Learning unknown ODE models with Gaussian processes. Aaltodoc (Aalto University). 1959–1968. 3 indexed citations

16.

Tsagaratou, Ageliki, Edahí González‐Avalos, Sini Rautio, et al.. (2016). TET proteins regulate the lineage specification and TCR-mediated expansion of iNKT cells. Nature Immunology. 18(1). 45–53. 110 indexed citations

17.

Yue, Xiaojing, Sara Trifari, Tarmo Äijö, et al.. (2016). Control of Foxp3 stability through modulation of TET activity. The Journal of Experimental Medicine. 213(3). 377–397. 265 indexed citations

18.

Heinonen, Markus, et al.. (2016). Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo. International Conference on Artificial Intelligence and Statistics. 732–740. 16 indexed citations

19.

Tsagaratou, Ageliki, Tarmo Äijö, Chan‐Wang Jerry Lio, et al.. (2014). Dissecting the dynamic changes of 5-hydroxymethylcytosine in T-cell development and differentiation. Proceedings of the National Academy of Sciences. 111(32). E3306–15. 138 indexed citations

20.

Laurila, Kirsti & Harri Lähdesmäki. (2009). Systematic Analysis of Disease-Related Regulatory Mutation Classes Reveals Distinct Effects on Transcription Factor Binding. In Silico Biology. 9(4). 209–224. 10 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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