Kalliokoski T - Search Results

1

Effects of nutrient optimization on intra-annual wood formation in Norway spruce.

Kalliokoski T, Mäkinen H, Jyske T, Nöjd P, Linder S. Kalliokoski T, et al. Tree Physiol. 2013 Nov;33(11):1145-55. doi: 10.1093/treephys/tpt078. Epub 2013 Oct 28. Tree Physiol. 2013. PMID: 24169103

2

Early root growth and architecture of fast- and slow-growing Norway spruce (Picea abies) families differ-potential for functional adaptation.

Hamberg L, Velmala SM, Sievänen R, Kalliokoski T, Pennanen T. Hamberg L, et al. Among authors: kalliokoski t. Tree Physiol. 2018 Jun 1;38(6):853-864. doi: 10.1093/treephys/tpx159. Tree Physiol. 2018. PMID: 29253241

3

The effect of tree architecture on conduit diameter and frequency from small distal roots to branch tips in Betula pendula, Picea abies and Pinus sylvestris.

Lintunen A, Kalliokoski T. Lintunen A, et al. Among authors: kalliokoski t. Tree Physiol. 2010 Nov;30(11):1433-47. doi: 10.1093/treephys/tpq085. Tree Physiol. 2010. PMID: 21030407

4

Effects of timing of soil frost thawing on Scots pine.

Repo T, Kalliokoski T, Domisch T, Lehto T, Mannerkoski H, Sutinen S, Finér L. Repo T, et al. Among authors: kalliokoski t. Tree Physiol. 2005 Aug;25(8):1053-62. doi: 10.1093/treephys/25.8.1053. Tree Physiol. 2005. PMID: 15929936

5

Current-year shoot hydraulic structure in two boreal conifers-implications of growth habit on water potential.

Mäkelä A, Grönlund L, Schiestl-Aalto P, Kalliokoski T, Hölttä T. Mäkelä A, et al. Among authors: kalliokoski t. Tree Physiol. 2019 Dec 1;39(12):1995-2007. doi: 10.1093/treephys/tpz107. Tree Physiol. 2019. PMID: 31728541

6

Extending the range of applicability of the semi-empirical ecosystem flux model PRELES for varying forest types and climate.

Tian X, Minunno F, Cao T, Peltoniemi M, Kalliokoski T, Mäkelä A. Tian X, et al. Among authors: kalliokoski t. Glob Chang Biol. 2020 May;26(5):2923-2943. doi: 10.1111/gcb.14992. Epub 2020 Mar 6. Glob Chang Biol. 2020. PMID: 31943608

7

Discovery of novel cannabinoid receptor ligands by a virtual screening approach: further development of 2,4,6-trisubstituted 1,3,5-triazines as CB2 agonists.

Yrjölä S, Kalliokoski T, Laitinen T, Poso A, Parkkari T, Nevalainen T. Yrjölä S, et al. Among authors: kalliokoski t. Eur J Pharm Sci. 2013 Jan 23;48(1-2):9-20. doi: 10.1016/j.ejps.2012.10.020. Epub 2012 Nov 3. Eur J Pharm Sci. 2013. PMID: 23131798

8

FieldChopper, a new tool for automatic model generation and virtual screening based on molecular fields.

Kalliokoski T, Ronkko T, Poso A. Kalliokoski T, et al. J Chem Inf Model. 2008 Jun;48(6):1131-7. doi: 10.1021/ci700216u. Epub 2008 May 20. J Chem Inf Model. 2008. PMID: 18489083

9

The effect of ligand-based tautomer and protomer prediction on structure-based virtual screening.

Kalliokoski T, Salo HS, Lahtela-Kakkonen M, Poso A. Kalliokoski T, et al. J Chem Inf Model. 2009 Dec;49(12):2742-8. doi: 10.1021/ci900364w. J Chem Inf Model. 2009. PMID: 19928753

10

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs.

Khan SA, Faisal A, Mpindi JP, Parkkinen JA, Kalliokoski T, Poso A, Kallioniemi OP, Wennerberg K, Kaski S. Khan SA, et al. Among authors: kalliokoski t. BMC Bioinformatics. 2012 May 30;13:112. doi: 10.1186/1471-2105-13-112. BMC Bioinformatics. 2012. PMID: 22646858 Free PMC article.

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