A complete list of publications can be found on PubMed

Selected recent publications


Smolander J, Junttila S, Elo LL. Cell-connectivity-guided trajectory inference from single-cell data. Bioinformatics 39(9):btad515, 2023.

Wang N, Khan S, Elo LL. VarSCAT: A computational tool for sequence context annotations of genomic variants. PLoS Comput Biol 19(8):e1010727, 2023.

Moulder R, Välikangas T, Hirvonen MK, Suomi T, Brorsson CA, Lietzén N, Bruggraber SFA, Overbergh L, Dunger DB, Peakman M, Chmura PJ, Brunak S, Schulte AM, Mathieu C, Knip M, Elo LL, Lahesmaa R. Targeted Serum Proteomics of Longitudinal Samples from Newly Diagnosed Youths with Type 1 Diabetes Distinguishes Markers of Disease and C-peptide Trajectory. To appear in Diabetologia.

Suomi T, Starskaia I, Kalim UU, Rasool O, Jaakkola MK, Grönroos T, Välikangas T, Brorson C, Mazzoni G, Bruggraber S, Overbergh L, Dunger D, Peakman M, Chmura P, Brunak S, Schulte AM, Mathieu C, Knip M, Lahesmaa R, Elo LL. Gene Expression Signature Predicts Rate of Type 1 Diabetes Progression. eBioMedicine 92:104625, 2023.

Jalkanen J, Khan S, Elima K, Huttunen T, Wang N, Hollmen M, Elo LL, Jalkanen S. Polymorphism in Interferon alpha/beta receptor contributes to glucocorticoid response and outcome of ARDS and COVID-19. Crit Care 27(1):112, 2023.


Välikangas T, Suomi T, Chandler CE, Scott AJ, Tran BQ, Ernst RK, Goodlett DR, Elo LL. Benchmarking tools for detecting longitudinal differential expression in proteomics data allows establishing a robust reproducibility optimization regression approach. Nat Commun 13(1):7877, 2022.

Rytkönen K, Adossa N, Mahmoudian M, Lönnberg T, Poutanen M, Elo LL. Cell type markers indicate distinct contributions of decidual stromal cells and natural killer cells in preeclampsia. Reproduction 164(5):V9-V13, 2022.

Kleino I, Frolovaite P, Suomi T, Elo LL. Computational Solutions for Spatial Transcriptomics. Comput Struct Biotechnol J 20:4870-4884, 2022.

Junttila S, Smolander J, Elo LL. Benchmarking methods for detecting differential states between conditions from multi-subject single-cell RNA-seq data. Brief Bioinform. 23(5):bbac286, 2022.

Pietilä S, Suomi T, Elo LL. Introducing untargeted data-independent acquisition for metaproteomics of complex microbial samples. ISME Commun. 2:51, 2022.

Välikangas T, Junttila S, Rytkönen KT, Kukkonen-Macchi A, Suomi T, Elo LL. COVID-19 specific transcriptomic signature detectable in blood across multiple cohorts. Front Genet 13:929887, 2022.

Shetty A, Tripathi SK, Junttila S, Buchacher T, Biradar R, Bhosale SD, Envall T, Laiho A, Moulder R, Rasool O, Galande S, Elo LL, Lahesmaa R. A systematic comparison of FOSL1, FOSL2 and BATF-mediated transcriptional regulation during early human Th17 differentiation. Nucleic Acids Res 50(9):4938-4958, 2022.

Khan MM, Khan MH, Kalim UU, Khan S, Junttila S, Paulin N, Kong L, Rasool O, Elo LL, Lahesmaa R. Long Intergenic Noncoding RNA MIAT as a Regulator of Human Th17 Cell Differentiation. Front Immunol 13:856762, 2022.

Suomi T, Elo LL. Statistical and machine learning methods to study human CD4+ T cell proteome profiles. Immunol Lett 245:8-17, 2022.

Välikangas T, Lietzén N, Jaakkola MK, Krogvold L, Eike MC, Kallionpää H, Tuomela S, Mathews C, Gerling IC, Oikarinen S, Hyöty H, Dahl-Jorgensen K, Elo LL, Lahesmaa R. Pancreas whole tissue transcriptomics highlights the role of the exocrine pancreas in patients with recently diagnosed type 1 diabetes. Front Endocrinol 13:861985, 2022.

Suomi T, Kalim UU, Rasool O, Laiho A, Kallionpää H, Vähä-Mäkilä M, Nurmio M, Mykkänen J, Härkönen T, Hyöty H, Ilonen J, Veijola R, Toppari J, Knip M, Elo LL, Lahesmaa R. Type 1 Diabetes in Children With Genetic Risk May Be Predicted Very Early With a Blood miRNA. Diabetes Care 45(4):e77-e79, 2022.

Rytkönen KT, Faux T, Mahmoudian M, Heinosalo T, Nnamani MC, Perheentupa A, Poutanen M, Elo LL, Wagner GP. Histone H3K4me3 breadth in hypoxia reveals endometrial core functions and stress adaptation linked to endometriosis. iScience 25(5):104235, 2022.

Ammunét T, Wang N, Khan S, Elo LL. Deep learning tools are top performers in long non-coding RNA prediction. Brief Funct Genomics 21(3):230-241, 2022.

Wang N, Lysenkov V, Orte K, Kairisto V, Aakko J, Khan S, Elo LL. Tool evaluation for the detection of variably sized indels from next generation whole genome and targeted sequencing data. PLoS Comput Biol 18(2):e1009269, 2022.

Jaakkola MK, Elo LL. Estimating cell type specific differential expression using deconvolution. Brief Bioinform 23(1):bbab433, 2022.

Hong Y, Flinkman D, Suomi T, Pietilä S, James P, Coffey E, Elo LL. PhosPiR: An automated phosphoproteomic pipeline in R. Brief Bioinform 23(1):bbab510, 2022.

Venäläinen MS, Heervä E, Hirvonen O, Saraei S, Suomi T, Mikkola T, Bärlund M, Jyrkkiö S, Laitinen T, Elo LL. Improved risk prediction of chemotherapy-induced neutropenia – model development and validation with real-world data. Cancer Med 11(3):654-663, 2022.


Smolander J, Junttila S, Venäläinen MS, Elo LL. scShaper: an ensemble method for fast and accurate linear trajectory inference from single-cell RNA-seq data. Bioinformatics 38(5):1328-35, 2021.

Mahmoudian M, Venäläinen MS, Klén R, Elo LL. Stable Iterative Variable Selection. Bioinformatics 37(24):4810-7, 2021.

Faux T, Rytkönen K, Mahmoudian M, Paulin N, Junttila S, Laiho A, Elo LL. Differential ATAC-seq and ChIP-seq peak detection using ROTS. NAR Genom Bioinform 3(3):lqab059, 2021.

Adossa N, Khan S, Rytkönen K, Elo LL. Computational strategies for single-cell multi-omics integration. Comput Struct Biotechnol J 19:2588-2596, 2021.

Jaakkola MK, Elo LL. Computational deconvolution to estimate cell type-specific gene expression from bulk data. NAR Genom Bioinform 3(1):lqaa110, 2021.

Smolander J, Junttila S, Venäläinen MS, Elo LL. ILoReg: a tool for high-resolution cell population identification from single-cell RNA-seq data. Bioinformatics 37(8):1107-1114, 2021.

Mehmood A, Laiho A, Elo LL. Exon-level estimates improve the detection of differentially expressed genes in RNA-seq studies. RNA Biology 1-8, 2021.

Mattila KE, Laajala TD, Tornberg SV, Kilpeläinen TP, Vainio P, Ettala O, Boström PJ, Nisen H, Elo LL, Jaakkola PM*. A Three-feature Prediction Model for Metastasis-free Survival after Surgery of Localized Clear Cell Renal Cell Carcinoma. Sci Rep 11(1):8650, 2021.

Smolander J, Khan S, Singaravelu K, Kauko L, Lund RJ, Laiho A, Elo LL. Evaluation of tools for identifying large copy number variations from ultra-low-coverage whole-genome sequencing data. BMC Genomics 22(1):357, 2021.

Sieberts SK, Schaff J, Duda M, Pataki BA, Sun M, Snyder P, Daneault JF, Parisi F, Costante G, Rubin U, Banda P, Chae Y, Neto EC, Dorsey ER, Aydın Z, Chen A, Elo LL, Espino C, Glaab E, Goan E, Golabchi FN, Görmez Y, Jaakkola MK, Jonnagaddala J, Klén R, Li D, McDaniel C, Perrin D, Perumal TM, Rad NM, Rainaldi E, Sapienza S, Schwab P, Shokhirev N, Venäläinen MS, Vergara-Diaz G,Zhang Y, the Parkinson’s Disease Digital Biomarker Challenge Consortium, Wang Y, Guan Y, Brunner D, Bonato P, Mangravite LM, Omberg L. Crowdsourcing digital health measures to predict Parkinson’s disease severity: the Parkinson’s Disease Digital Biomarker DREAM Challenge. NPJ Digit Med 4(1):53, 2021.

Venäläinen MS, Panula VJ, Klén R, Haapakoski JJ, Eskelinen AP, Manninen MJ, Kettunen JS, Puhto AP, Vasara AI, Mäkelä KT, Elo LL. Development of Preoperative Risk Prediction Models for Short-Term Revision and Death Following Total Hip Arthroplasty Using data from the Finnish Arthroplasty Register. JB JS Open Access 6(1):e20.00091, 2021.

Mokkala K, Paulin N, Houttu N, Koivuniemi E, Pellonperä O, Khan S, Pietilä S, Tertti K, Elo LL, Laitinen K. Metagenomics analysis of gut microbiota in response to diet intervention and gestational diabetes in overweight and obese women: a randomised, double-blind, placebo-controlled clinical trial. Gut 70(2):309-318, 2021.


Mehmood A, Laiho A, Venäläinen MS, McGlinchey AJ, Wang N, Elo LL. Systematic evaluation of differential splicing tools for RNA-seq studies. Brief Bioinform 21(6):2052-2065, 2020.

Suni V, Seyednasrollah F, Ghimire B, Junttila S, Laiho A, Elo LL. Reproducibility-optimized detection of differential DNA methylation. Epigenomics 12(9):747-755, 2020.

Khan S, Ince-Dunn G, Suomalainen A, Elo LL. Integrative omics approaches provide biological and clinical insights: examples from mitochondrial diseases. J Clin Invest 130(1):20-28, 2020.

Venäläinen MS, Klén R, Mahmoudian M, Raitakari OT, Elo LL. Easy-to-use tool for evaluating the elevated acute kidney injury risk against reduced cardiovascular disease risk during intensive blood pressure control. J Hypertens 38(3):511-518, 2020.

Klén R, Karhunen M, Elo LL. Likelihood contrasts: a machine learning algorithm for binary classification of longitudinal data. Sci Rep 10(1):1016, 2020.

Aakko J, Pietilä S, Suomi T, Mahmoudian M, Toivonen R, Kouvonen P, Rokka A, Hänninen A, Elo LL. Data-independent acquisition mass spectrometry in metaproteomics of gut microbiota – implementation and computational analysis. J Proteome Res 19(1):432-436, 2020.

Yang M, Petralia F, Li Z, Li H, Ma W, Song X, Kim S, Lee H, Yu H, Lee B, Bae S, Heo E, Kaczmarczyk J, Stępniak P, Warchoł M, Yu T, Calinawan AP, Boutros PC, Payne SH, Reva B, NCI-CPTAC-DREAM Consortium Group, Boja E, Rodriguez H, Stolovitzky G, Guan Y, Kang J, Wang P, Fenyo D, Saez-Rodriguez J. Assessment of the Limits of Predictability of Protein and Phosphorylation Levels in Cancer. Cell Syst 11(2):186-195.e9, 2020.


Chakroborty D, Emani MR, Klén R, Böckelman C, Hagström J, Haglund C, Ristimäki A, Lahesmaa R, Elo LL. L1TD1 – A Prognostic Marker for Colon Cancer. BMC Cancer 19(1):727, 2019.

Chakroborty D, Kurppa KJ, Paatero I, Ojala VK, Koivu M, Tamirat MZ, Koivunen JP, Jänne PA, Johnson MS, Elo LL, Elenius K. An unbiased in vitro screen for activating epidermal growth factor receptor mutations. J Biol Chem 294(24):9377-9389, 2019.

Pietilä S, Suomi T, Aakko J, Elo LL. A Data Analysis Protocol for Quantitative Data-Independent Acquisition Proteomics. Methods Mol Biol 1871:455-465, 2019.

Faux T, Rytkönen KT, Laiho A, Elo LL. RepViz: A replicate-driven R tool for visualizing genomic regions. BMC Res Notes 12(1):441, 2019.

Tripathi SK, Välikangas T, Shetty A, Khan MM, Moulder R, Bhosale SD, Komsi E, Salo V, De Albuquerque RS, Rasool O, Galande S, Elo LL, Lahesmaa R*. Quantitative Proteomics Reveals the Dynamic Protein Landscape during Initiation of Human Th17 Cell Polarization. iScience 11:334-355, 2019.


Välikangas T, Suomi T, Elo LL. A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation. Brief Bioinform 19(6):1344-1355, 2018.

Fourati S, Talla A, Mahmoudian M, Burkhart JG, Klén R, Henao R, Yu T, Aydın Z, Yeung KY, Ahsen ME, Almugbel R, Jahandideh S, Liang X, Nordling TEM, Shiga M, Stanescu A, Vogel R, The Respiratory Viral DREAM Challenge Consortium, Pandey G, Chiu C, McClain MT, Woods CW, Ginsburg GS, Elo LL, Tsalik EL, Mangravite LM, Sieberts SK. A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection. Nat Commun 9(1):4418, 2018.

Jaakkola MK, McGlinchey AJ, Klen R, Elo LL. PASI: a novel pathway method to identify delicate group effects. PLoS One 13(7):e0199991, 2018.

Välikangas T, Suomi T, Elo LL. A systematic evaluation of normalisation methods in quantitative label-free proteomics. Brief Bioinform 19(1):1-11, 2018.

Suni V, Suomi T, Tsubosaka T, Imanishi SY, Elo LL, Corthals GL. SimPhospho: a software tool enabling confident phosphosite assignment. Bioinformatics 34(15):2690-2692, 2018.

Saraei S, Suomi T, Kauko O, Elo LL. Phosphonormalizer: an R package for normalization of MS-based label-free phosphoproteomics. Bioinformatics 34(4):693-694, 2018.

Lietzen N, An LTT, Jaakkola MK, Kallionpää H, Oikarinen S, Mykkänen J, Knip M, Veijola R, Ilonen J, Toppari J, Hyöty H, Lahesmaa R, Elo LL*. Enterovirus-Associated Changes in Blood Transcriptomic Profiles of Children with Genetic Susceptibility to Type 1 Diabetes. Diabetologia 61(2):381-388, 2018.


Seyednasrollah F, Koestler DC, Wang T, Piccolo SR, Vega R, Greiner R, Fuchs C, Gofer E, Kumar L, Wolfinger RD, Winner KK, Bare C, Neto EC, Yu T, Shen L, Abdallah K, Norman T, Stolovitzky G, PCC-DREAM Community, Soule H, Sweeney CJ, Ryan CJ, Scher HI, Sartor O, Elo LL, Zhou FL, Guinney J, Costello JC. A DREAM Challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration-resistant prostate cancer. JCO Clin Cancer Inform 1:1-15, 2017.

Rautakorpi LK, Seyednasrollah F, Mäkelä J, Hirvonen OM, Laitinen T, Elo LL, Jyrkkiö SM. End-of-life Chemotherapy use at a Finnish University Hospital; a Retrospective Cohort Study. Acta Oncol 56(10):1272-1276, 2017.

Seyednasrollah F, Mahmoudian M, Rautakorpi L, Hirvonen O, Laitinen T, Jyrkkiö S, Elo LL. How reliable are trial-based prognostic models in real-world patients with metastatic castration resistant prostate cancer? Eur Urol 71(5):838-840, 2017.

Seyednasrollah F, Mäkelä J, Pitkänen N, Juonala M, Hutri-Kähönen N, Lehtimäki T, Viikari J, Kelly T, Li C, Bazzano L, Elo LL, Raitakari OT*. Prediction of adulthood obesity using genetic and childhood clinical risk factors in the Cardiovascular Risk in Young Finns Study. Circ Cardiovasc Genet 10(3):e001554, 2017.

Jaakkola MK, Seyednasrollah F, Mehmood A, Elo LL. Comparison of methods to detect differentially expressed genes between single-cell populations. Brief Bioinform 18(5):735-743, 2017.

Suomi T, Elo LL. Enhanced differential expression statistics for data-independent acquisition proteomics. Sci Rep 7(1):5869, 2017.

Suomi T, Seyednasrollah F, Jaakkola MK, Faux T, Elo LL. ROTS: An R Package for Reproducibility-Optimized Statistical Testing. PLoS Comput Biol 13(5):e1005562, 2017.


Laajala TD, Seikkula H, Seyednasrollah F, Mirtti T, Boström PJ, Elo LL. Longitudinal modeling of ultrasensitive and traditional prostate-specific antigen and prediction of biochemical recurrence after radical prostatectomy. Sci Rep 6:36161, 2016.

Jaakkola MK, Elo LL. Empirical comparison of structure-based pathway methods. Brief Bioinform 17(2):336-45, 2016.

Seyednasrollah F, Rantanen K, Jaakkola P, Elo LL. ROTS: reproducible RNA-seq biomarker detector – prognostic markers for clear cell renal cell cancer. Nucleic Acids Res 44(1):e1, 2016.

Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A, McPherson A, Szczesniak MW, Gaffney DJ, Elo LL, Zhang X, Mortazavi A. A survey of best practices for RNA-seq data analysis. Genome Biol 17(1):13, 2016.


Suomi T, Corthals GL, Nevalainen OS, Elo LL. Using peptide-level proteomics data for detecting differentially expressed proteins. J Proteome Res 14(11):4564-70, 2015.

Pursiheimo A, Vehmas AP, Afzal S, Suomi T, Chand T, Strauss L, Poutanen M, Rokka A, Corthals GL, Elo LL. Optimization of Statistical Methods Impact on Quantitative Proteomics Data. J Proteome Res 14(10):4118-26, 2015.

Seyednasrollah F, Laiho A, Elo LL. Comparison of software packages for detecting differential expression in RNA-seq studies. Brief Bioinform 16(1): 59-70, 2015.

Laiho A, Elo LL. A note on an exon-based strategy to identify differentially expressed genes in RNA-seq experiments. PLoS One 9(12): e115964, 2014.

Kallionpää H, Elo LL, Laajala E, Mykkänen J, Ricaño-Ponce I, Vaarma M, Laajala TD, Hyöty H, Ilonen J, Veijola R, Simell T, Wijmenga C, Knip M, Lähdesmäki H, Simell O, Lahesmaa R. Innate immune activity is detected prior to seroconversion in children with HLA-conferred type 1 diabetes susceptibility. Diabetes 63: 2402-2414, 2014.

Elo LL and Schwikowski B. Analysis of Time-Resolved Gene Expression Measurements Across Individuals. PLoS One 8(12): e82340, 2013.

Kallio A, Elo LL. Optimizing Detection of Transcription Factor-Binding Sites in ChIP-seq Experiments. Methods Mol Biol 1038: 181-91, 2013.

Elo LL, Schwikowski B. Mining proteomic data for biomedical research. WIREs Data Mining Knowl Discov 2: 1-13, 2012.

Elo LL, Järvenpää H, Tuomela S, Raghav S*, Ahlfors H, Laurila K, Gupta B, Lund RJ, Tahvanainen J, Hawkins RD, Oresic M, Lähdesmäki H, Rasool O, Rao KV, Aittokallio T, Lahesmaa R. Genome-wide profiling of interleukin-4 and STAT6 transcription factor regulation of human Th2 cell programming. Immunity 32: 852-862, 2010.

Laajala E, Aittokallio T, Lahesmaa R, Elo LL. Probe-level estimation improves the detection of differential splicing in Affymetrix exon array studies. Genome Biol 10: R77, 2009.

Laajala TD, Raghav S, Tuomela S, Lahesmaa R, Aittokallio T, Elo LL. A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments. BMC Genomics 10:618, 2009.