Heinonen M - Search Results

1

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. Cichonska A, et al. Among authors: heinonen m. Bioinformatics. 2018 Jul 1;34(13):i509-i518. doi: 10.1093/bioinformatics/bty277. Bioinformatics. 2018. PMID: 29949975 Free PMC article.

2

FiD: a software for ab initio structural identification of product ions from tandem mass spectrometric data.

Heinonen M, Rantanen A, Mielikäinen T, Kokkonen J, Kiuru J, Ketola RA, Rousu J. Heinonen M, et al. Rapid Commun Mass Spectrom. 2008 Oct;22(19):3043-52. doi: 10.1002/rcm.3701. Rapid Commun Mass Spectrom. 2008. PMID: 18763276

3

Computing atom mappings for biochemical reactions without subgraph isomorphism.

Heinonen M, Lappalainen S, Mielikäinen T, Rousu J. Heinonen M, et al. J Comput Biol. 2011 Jan;18(1):43-58. doi: 10.1089/cmb.2009.0216. J Comput Biol. 2011. PMID: 21210731

4

Metabolite identification and molecular fingerprint prediction through machine learning.

Heinonen M, Shen H, Zamboni N, Rousu J. Heinonen M, et al. Bioinformatics. 2012 Sep 15;28(18):2333-41. doi: 10.1093/bioinformatics/bts437. Epub 2012 Jul 18. Bioinformatics. 2012. PMID: 22815355

5

Metabolite Identification through Machine Learning- Tackling CASMI Challenge Using FingerID.

Shen H, Zamboni N, Heinonen M, Rousu J. Shen H, et al. Among authors: heinonen m. Metabolites. 2013 Jun 6;3(2):484-505. doi: 10.3390/metabo3020484. Metabolites. 2013. PMID: 24958002 Free PMC article.

6

mGPfusion: predicting protein stability changes with Gaussian process kernel learning and data fusion.

Jokinen E, Heinonen M, Lähdesmäki H. Jokinen E, et al. Among authors: heinonen m. Bioinformatics. 2018 Jul 1;34(13):i274-i283. doi: 10.1093/bioinformatics/bty238. Bioinformatics. 2018. PMID: 29949987 Free PMC article.

7

Bayesian metabolic flux analysis reveals intracellular flux couplings.

Heinonen M, Osmala M, Mannerström H, Wallenius J, Kaski S, Rousu J, Lähdesmäki H. Heinonen M, et al. Bioinformatics. 2019 Jul 15;35(14):i548-i557. doi: 10.1093/bioinformatics/btz315. Bioinformatics. 2019. PMID: 31510676 Free PMC article.

8

Substrate specificity of 2-deoxy-D-ribose 5-phosphate aldolase (DERA) assessed by different protein engineering and machine learning methods.

Voutilainen S, Heinonen M, Andberg M, Jokinen E, Maaheimo H, Pääkkönen J, Hakulinen N, Rouvinen J, Lähdesmäki H, Kaski S, Rousu J, Penttilä M, Koivula A. Voutilainen S, et al. Among authors: heinonen m. Appl Microbiol Biotechnol. 2020 Dec;104(24):10515-10529. doi: 10.1007/s00253-020-10960-x. Epub 2020 Nov 4. Appl Microbiol Biotechnol. 2020. PMID: 33147349 Free PMC article.

9

TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifs.

Jokinen E, Dumitrescu A, Huuhtanen J, Gligorijević V, Mustjoki S, Bonneau R, Heinonen M, Lähdesmäki H. Jokinen E, et al. Among authors: heinonen m. Bioinformatics. 2023 Jan 1;39(1):btac788. doi: 10.1093/bioinformatics/btac788. Bioinformatics. 2023. PMID: 36477794 Free PMC article.

10

Predicting recognition between T cell receptors and epitopes with TCRGP.

Jokinen E, Huuhtanen J, Mustjoki S, Heinonen M, Lähdesmäki H. Jokinen E, et al. Among authors: heinonen m. PLoS Comput Biol. 2021 Mar 25;17(3):e1008814. doi: 10.1371/journal.pcbi.1008814. eCollection 2021 Mar. PLoS Comput Biol. 2021. PMID: 33764977 Free PMC article.

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