Professorship Lähdesmäki H.

Research Output

2020

Accounting for environmental variation in co-occurrence modelling reveals the importance of positive interactions in root-associated fungal communities

Abrego, N., Roslin, T., Huotari, T., Tack, A. J. M., Lindahl, B. D., Tikhonov, G., Somervuo, P., Schmidt, N. M. & Ovaskainen, O., 1 Jan 2020, In : MOLECULAR ECOLOGY.

Research output: Contribution to journalArticleScientificpeer-review

Open Access

A personalised approach for identifying disease-relevant pathways in heterogeneous diseases

Somani, J., Ramchandran, S. & Lähdesmäki, H., 1 Dec 2020, In : npj Systems Biology and Applications. 6, 1, 17.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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1 Downloads (Pure)

Computationally efficient joint species distribution modeling of big spatial data

Tikhonov, G., Duan, L., Abrego, N., Newell, G., White, M., Dunson, D. & Ovaskainen, O., Feb 2020, In : ECOLOGY. 101, 2, e02929.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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3 Citations (Scopus)
24 Downloads (Pure)

Deep Convolutional Gaussian Processes

Blomqvist, K., Kaski, S. & Heinonen, M., 1 Jan 2020, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Proceedings. Brefeld, U., Fromont, E., Hotho, A., Knobbe, A., Maathuis, M. & Robardet, C. (eds.). SPRINGER , p. 582-597 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11907 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Enhancer prediction in the human genome by probabilistic modelling of the chromatin feature patterns

Osmala, M. & Lähdesmäki, H., 20 Jul 2020, In : BMC Bioinformatics. 21, 1, 37 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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Learning spectrograms with convolutional spectral kernels

Shen, Z., Heinonen, M. & Kaski, S., 2020, (Accepted/In press) The 23rd International Conference on Artificial Intelligence and Statistic. (Proceedings of Machine Learning Research).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Likelihood-Free Inference with Deep Gaussian Processes

Aushev, A., Pesonen, H., Heinonen, M., Corander, J. & Kaski, S., 18 Jun 2020, (Submitted).

Research output: Contribution to conferencePaperScientific

2019

A Mathematical Model for Enhancer Activation Kinetics During Cell Differentiation

Nousiainen, K., Intosalmi, J. & Lähdesmäki, H., 1 Jan 2019, Algorithms for Computational Biology - 6th International Conference, AlCoB 2019, Proceedings. Vega-Rodríguez, M. A., Holmes, I. & Martín-Vide, C. (eds.). p. 191-202 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11488 LNBI).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

An additive Gaussian process regression model for interpretable non-parametric analysis of longitudinal data

Cheng, L., Ramchandran, S., Vatanen, T., Lietzén, N., Lahesmaa, R., Vehtari, A. & Lähdesmäki, H., 17 Apr 2019, In : Nature Communications. 10, 1, p. 1-11 11 p., 1798.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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4 Citations (Scopus)
139 Downloads (Pure)

Bayesian metabolic flux analysis reveals intracellular flux couplings

Heinonen, M., Osmala, M., Mannerström, H., Wallenius, J., Kaski, S., Rousu, J. & Lähdesmäki, H., 15 Jul 2019, In : Bioinformatics. 35, 14, p. i548-i557 btz315.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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86 Downloads (Pure)

Data-driven multiscale modeling reveals the role of metabolic coupling for the spatio-temporal growth dynamics of yeast colonies

Intosalmi, J., Scott, A. C., Hays, M., Flann, N., Yli-Harja, O., Lähdesmäki, H., Dudley, A. M. & Skupin, A., 19 Dec 2019, In : BMC Molecular and Cell Biology. 20, 1, 59.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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25 Downloads (Pure)

Deep learning with differential Gaussian process flows

Hegde, P., Heinonen, M., Lähdesmäki, H. & Kaski, S., Apr 2019, The 22nd International Conference on Artificial Intelligence and Statistic. Vol. 89. p. 1-15 16 p. (Proceedings of Machine Learning Research; vol. 89).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
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27 Downloads (Pure)

Early detection of peripheral blood cell signature in children developing β-cell autoimmunity at a young age

Kallionpää, H., Somani, J., Tuomela, S., Ullah, U., De Albuquerque, R., Lönnberg, T., Komsi, E., Siljander, H., Honkanen, J., Härkönen, T., Peet, A., Tillmann, V., Chandra, V., Anagandula, M. K., Frisk, G., Otonkoski, T., Rasool, O., Lund, R., Lähdesmäki, H., Knip, M. & 1 others, Lahesmaa, R., 1 Oct 2019, In : DIABETES. 68, 10, p. 2024-2034 11 p.

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Enhancer prediction in the human genome by probabilistic modeling of the chromatin feature patterns

Osmala, M. & Lähdesmäki, H., 17 Oct 2019, (Submitted) In : Springer.

Research output: Contribution to journalArticleScientificpeer-review

Genomic variation and strain-specific functional adaptation in the human gut microbiome during early life

Vatanen, T., Plichta, D. R., Somani, J., Münch, P. C., Arthur, T. D., Hall, A. B., Rudolf, S., Oakeley, E. J., Ke, X., Young, R. A., Haiser, H. J., Kolde, R., Yassour, M., Luopajärvi, K., Siljander, H., Virtanen, S. M., Ilonen, J., Uibo, R., Tillmann, V., Mokurov, S. & 8 others, Dorshakova, N., Porter, J. A., McHardy, A. C., Lähdesmäki, H., Vlamakis, H., Huttenhower, C., Knip, M. & Xavier, R. J., 1 Mar 2019, In : Nature Microbiology. 4, 3, p. 470-479

Research output: Contribution to journalArticleScientificpeer-review

22 Citations (Scopus)

Joint species distribution modelling with the R-package Hmsc

Tikhonov, G., Opedal, Ø. H., Abrego, N., Lehikoinen, A., de Jonge, M. M. J., Oksanen, J. & Ovaskainen, O., 25 Dec 2019, In : Methods in Ecology and Evolution. 11, 3, p. 442-447

Research output: Contribution to journalArticleScientificpeer-review

Open Access
7 Citations (Scopus)

ODE2VAE: Deep generative second order ODEs with Bayesian neural networks

Yildiz, C., Heinonen, M. & Lähdesmäki, H., 2019, 33rd Conference on Neural Information Processing Systems: NeurIPS 2019 . Neural Information Processing Systems Foundation, (Advances in Neural Information Processing Systems).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access

Peripheral blood DNA methylation differences in twin pairs discordant for Alzheimer's disease

Konki, M., Malonzo, M., Karlsson, I. K., Lindgren, N., Ghimire, B., Smolander, J., Scheinin, N. M., Ollikainen, M., Laiho, A., Elo, L. L., Lonnberg, T., Roytta, M., Pedersen, N. L., Kaprio, J., Lahdesmaki, H., Rinne, J. O. & Lund, R. J., 2 Sep 2019, In : Clinical epigenetics. 11, 1, 12 p., 130.

Research output: Contribution to journalArticleScientificpeer-review

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38 Downloads (Pure)

TimeRank: A random walk approach for community discovery in dynamic networks

Sarantopoulos, I., Papatheodorou, D., Vogiatzis, D., Tzortzis, G. & Paliouras, G., 1 Jan 2019, Complex Networks and Their Applications VII - Volume 1 Proceedings The 7th International Conference on Complex Networks and their Applications COMPLEX NETWORKS 2018. Lambiotte, R., Rocha, L. M., Lió, P., Cherifi, H., Aiello, L. M. & Cherifi, C. (eds.). p. 338-350 13 p. (Studies in Computational Intelligence; vol. 812).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

1 Citation (Scopus)
2018

A Nonparametric Spatio-temporal SDE Model

Yildiz, C., Heinonen, M. & Lähdesmäki, H., 2018, NIPS 2018 Spatiotemporal Workshop: 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montréal, Canada. Neural Information Processing Systems Foundation, p. 1-5

Research output: Chapter in Book/Report/Conference proceedingConference contributionProfessional

Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization

Simsekli, U., Yildiz, C., Nguyen, T. H., Richard, G. & Cemgil, A. T., 2018, Proceedings of the 35th International Conference on Machine Learning. p. 4681-4690 (Proceedings of Machine Learning Research; vol. 80).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
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2 Downloads (Pure)

Asynchronous stochastic Quasi-Newton MCMC for non-convex optimization supplementary document

Simsekli, U., Yildiz, C., Nguyen, T. H., Richard, G. & Cemgil, A. T., 1 Jan 2018, 35th International Conference on Machine Learning, ICML 2018. Krause, A. & Dy, J. (eds.). Vol. 11. p. 4674-4683 8 p. (Proceedings of Machine Learning Research; vol. 80).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
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10 Downloads (Pure)

Atopic asthma after rhinovirus-induced wheezing is associated with DNA methylation change in the SMAD3 gene promoter

Lund, R. J., Osmala, M., Malonzo, M., Lukkarinen, M., Leino, A., Salmi, J., Vuorikoski, S., Turunen, R., Vuorinen, T., Akdis, C., Lähdesmäki, H., Lahesmaa, R. & Jartti, T., 5 May 2018, In : Allergy. 73, 8, p. 1735-1740 6 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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15 Citations (Scopus)
129 Downloads (Pure)

Characterization and non-parametric modeling of the developing serum proteome during infancy and early childhood

Lietzén, N., Cheng, L., Moulder, R., Siljander, H., Laajala, E., Härkönen, T., Peet, A., Vehtari, A., Tillmann, V., Knip, M., Lähdesmäki, H. & Lahesmaa, R., 1 Dec 2018, In : Scientific Reports. 8, 1, p. 1-13 5883.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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3 Citations (Scopus)
135 Downloads (Pure)

Flex ddG: Rosetta Ensemble-Based Estimation of Changes in Protein–Protein Binding Affinity upon Mutation

Barlow, K., Conchuir, S., Thompson, S., Suresh, P., Lucas, J., Heinonen, M. & Kortemme, T., 31 May 2018, In : Journal of Physical Chemistry B. 122, 21, p. 5389-5399 11 p.

Research output: Contribution to journalArticleScientificpeer-review

23 Citations (Scopus)

Generative models for quantification of DNA modifications

Äijö, T., Bonneau, R. & Lähdesmäki, H., 1 Jan 2018, Methods in Molecular Biology. p. 37-50 14 p. (Methods in Molecular Biology; vol. 1807).

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

1 Citation (Scopus)

Learning Stochastic Differential Equations With Gaussian Processes Without Gradient Matching

Yildiz, C., Heinonen, M., Intosalmi, J., Mannerström, H. & Lähdesmäki, H., 2018, IEEE International Workshop on Machine Learning for Signal Processing. IEEE, 6 p. 8516991

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)

Learning unknown ODE models with Gaussian processes

Heinonen, M., Yildiz, C., Mannerström, H., Intosalmi, J. & Lähdesmäki, H., 2018, Proceedings of the 35th International Conference on Machine Learning, ICML 2018. Vol. 5. p. 3120-3132 13 p. (Proceedings of Machine Learning Research; vol. 80).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
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1 Citation (Scopus)
19 Downloads (Pure)

Learning with multiple pairwise kernels for drug bioactivity prediction

Cichonska, A., Pahikkala, T., Szedmak, S., Julkunen, H., Airola, A., Heinonen, M., Aittokallio, T. & Rousu, J., 1 Jul 2018, In : Bioinformatics. 34, 13, p. i509-i518

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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4 Citations (Scopus)
73 Downloads (Pure)

MGPfusion: Predicting protein stability changes with Gaussian process kernel learning and data fusion

Jokinen, E., Heinonen, M. & Lähdesmäki, H., 1 Jul 2018, In : Bioinformatics. 34, 13, p. i274-i283

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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6 Citations (Scopus)
69 Downloads (Pure)

Quantitative proteomic characterization and comparison of T helper 17 and induced regulatory T cells

Mohammad, I., Nousiainen, K., Bhosale, S. D., Starskaia, I., Moulder, R., Rokka, A., Cheng, F., Mohanasundaram, P., Eriksson, J. E., Goodlett, D. R., Lähdesmäki, H. & Chen, Z., 31 May 2018, In : PLoS Biology. 16, 5, e2004194.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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3 Citations (Scopus)
128 Downloads (Pure)

snpEnrichR: analyzing co-localization of SNPs and their proxies in genomic regions

Nousiainen, K., Kanduri, K., Ricaño-Ponce, I., Wijmenga, C., Lahesmaa, R., Kumar, V. & Lähdesmäki, H., 1 Dec 2018, In : Bioinformatics (Oxford, England). 34, 23, p. 4112-4114 3 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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84 Downloads (Pure)

Temporal clustering analysis of endothelial cell gene expression following exposure to a conventional radiotherapy dose fraction using Gaussian process clustering

Heinonen, M., Milliat, F., Benadjaoud, M. A., François, A., Buard, V., Tarlet, G., D'Alché-Buc, F. & Guipaud, O., 1 Oct 2018, In : PloS one. 13, 10, p. 1-31 e0204960.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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132 Downloads (Pure)

The human gut microbiome in early-onset type 1 diabetes from the TEDDY study

Vatanen, T., Franzosa, E. A., Schwager, R., Tripathi, S., Arthur, T. D., Vehik, K., Lernmark, Å., Hagopian, W. A., Rewers, M. J., She, J. X., Toppari, J., Ziegler, A. G., Akolkar, B., Krischer, J. P., Stewart, C. J., Ajami, N. J., Petrosino, J. F., Gevers, D., Lähdesmäki, H., Vlamakis, H. & 2 others, Huttenhower, C. & Xavier, R. J., 25 Oct 2018, In : Nature. 562, 7728, p. 589-594 6 p.

Research output: Contribution to journalLetterScientificpeer-review

Open Access
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108 Citations (Scopus)
418 Downloads (Pure)

Time-resolved transcriptome and proteome landscape of human regulatory T cell (Treg) differentiation reveals novel regulators of FOXP3

Schmidt, A., Marabita, F., Kiani, N. A., Gross, C. C., Johansson, H. J., Éliás, S., Rautio, S., Eriksson, M., Fernandes, S. J., Silberberg, G., Ullah, U., Bhatia, U., Lähdesmäki, H., Lehtiö, J., Gomez-Cabrero, D., Wiendl, H., Lahesmaa, R. & Tegnér, J., 7 May 2018, In : BMC Biology. 16, 1, p. 1-35 47.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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6 Citations (Scopus)
173 Downloads (Pure)

Transcriptional Repressor HIC1 Contributes to Suppressive Function of Human Induced Regulatory T Cells

Ubaid Ullah, U., Andrabi, S. B. A., Tripathi, S. K., Dirasantha, O., Kanduri, K., Rautio, S., Gross, C. C., Lehtimäki, S., Bala, K., Tuomisto, J., Bhatia, U., Chakroborty, D., Elo, L. L., Lähdesmäki, H., Wiendl, H., Rasool, O. & Lahesmaa, R., 20 Feb 2018, In : Cell Reports. 22, 8, p. 2094-2106 13 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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12 Citations (Scopus)
130 Downloads (Pure)

Variational zero-inflated Gaussian processes with sparse kernels

Hegde, P., Heinonen, M. & Kaski, S., 2018, 34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018. AUAI Press, Vol. 1. p. 361-371 148

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
2017

Acquired Somatic Mutations in T Cells in Patients with Aplastic Anemia and Hypoplastic Myelodysplastic Syndromes

Lundgren, S., Keränen, M., Nousiainen, K., Eldfors, S., Hannula, S., Hannunen, T., Ellonen, P., Walldin, G., Clemente, M., Ebeling, F., Rajala, H., Maciejewski, J. P., Lähdesmäki, H., Hellstrom-Lindberg, E. & Mustjoki, S., 2017, In : BLOOD. 130, Suppl 1, p. 1169-1169 1 p.

Research output: Contribution to journalArticleScientificpeer-review

A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings

Remes, S., Heinonen, M. & Kaski, S., Nov 2017, Proceedings of the 9th Asian Conference on Machine Learning. Zhang, M-L. & Noh, Y-K. (eds.). p. 455-470 16 p. (Proceedings of Machine Learning Research; vol. 77).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
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34 Downloads (Pure)

Efficient statistical methods for detecting differential methylation

Halla-aho, V. & Lähdesmäki, H., 22 Jul 2017.

Research output: Contribution to conferencePaperScientific

File
18 Downloads (Pure)

Genome-wide Analysis of STAT3-Mediated Transcription during Early Human Th17 Cell Differentiation

Tripathi, S. K., Chen, Z., Larjo, A., Kanduri, K., Nousiainen, K., Äijo, T., Ricaño-Ponce, I., Hrdlickova, B., Tuomela, S., Laajala, E., Salo, V., Kumar, V., Wijmenga, C., Lähdesmäki, H. & Lahesmaa, R., 30 May 2017, In : Cell Reports. 19, 9, p. 1888-1901 14 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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19 Citations (Scopus)
148 Downloads (Pure)

High-throughput automated microfluidic sample preparation for accurate microbial genomics

Kim, S., De Jonghe, J., Kulesa, A. B., Feldman, D., Vatanen, T., Bhattacharyya, R. P., Berdy, B., Gomez, J., Nolan, J., Epstein, S. & Blainey, P. C., 27 Jan 2017, In : Nature Communications. 8, p. 1-10 13919.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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39 Citations (Scopus)
153 Downloads (Pure)

Metagenomic analyses of the human gut microbiome reveal connections to the immune system

Vatanen, T., 2017, Aalto University. 154 p.

Research output: ThesisDoctoral ThesisCollection of Articles

Open Access

Non-Stationary Spectral Kernels

Remes, S., Heinonen, M. & Kaski, S., 2017, Advances in Neural Information Processing Systems 30: Proceedings of NIPS2017. Curran Associates, Inc., p. 4645-4654 (Advances in Neural Information Processing Systems; vol. 30).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Open Access
12 Citations (Scopus)

RNA Polymerase III Subunit POLR3G Regulates Specific Subsets of PolyA+ and SmallRNA Transcriptomes and Splicing in Human Pluripotent Stem Cells

Lund, R. J., Rahkonen, N., Malonzo, M., Kauko, L., Emani, M. R., Kivinen, V., Närvä, E., Kemppainen, E., Laiho, A., Skottman, H., Hovatta, O., Rasool, O., Nykter, M., Lähdesmäki, H. & Lahesmaa, R., 9 May 2017, In : Stem Cell Reports. 8, 5, p. 1442-1454 13 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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2 Citations (Scopus)
95 Downloads (Pure)

TET2 and 3 proteins control iNKT cell lineage specification and TCR mediated expansion

Tsagaratou, A., Avalos, E. G., Rautio, S., Browne, J. S., Togher, S., Pastor, W., Rothenberg, E. V., Lahdesmaki, H. & Rao, A., 2017, In : JOURNAL OF IMMUNOLOGY. 198, 1, Supplement, p. 215.11

Research output: Contribution to journalArticleScientificpeer-review

TET proteins regulate the lineage specification and TCR-mediated expansion of iNKT cells

Tsagaratou, A., González-Avalos, E., Rautio, S., Scott-Browne, J. P., Togher, S., Pastor, W. A., Rothenberg, E. V., Chavez, L., Lähdesmäki, H. & Rao, A., 2017, In : NATURE IMMUNOLOGY. 18, 1, p. 45-53

Research output: Contribution to journalArticleScientificpeer-review

44 Citations (Scopus)
2016

A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways

Äijö, T., Huang, Y., Mannerström, H., Chavez, L., Tsagaratou, A., Rao, A. & Lähdesmäki, H., 14 Mar 2016, In : GENOME BIOLOGY. 17, 1, p. 1-22 49.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
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11 Citations (Scopus)
172 Downloads (Pure)

A subpopulation model to analyze heterogeneous cell differentiation dynamics

Chan, Y. H., Intosalmi, J., Rautio, S. & Lähdesmäki, H., 1 Nov 2016, In : Bioinformatics. 32, 21, p. 3306-3313 8 p.

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)