Cross-species translation of multi-way biomarkers (2011)
AUTHORS:
Suvitaival Tommi
,
Huopaniemi Ilkka,
Ore\vsi\vc Matej,
Kaski Samuel
BOOKTITLE:
Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN), Part I
SERIES:
Lecture Notes in Computer Science
VOLUME:
6791
PAGES:
209--216
URL:
http://dx.doi.org/10.1007/978-3-642-21735-7_26
INTERNALPDF:
internalpdf/suvitaival11.pdf
@inproceedings{ Suvitaival11, editor = "Honkela, Timo and Duch, Wlodzislaw and Girolami, Mark and Kaski, Samuel", author = "Suvitaival, Tommi and Huopaniemi, Ilkka and Ore{\v{s}}i{\v{c}}, Matej and Kaski, Samuel", publisher = "Springer", responsibleauthor = "Kaski, Samuel", language = "eng", title = "Cross-species translation of multi-way biomarkers", url = "http://dx.doi.org/10.1007/978-3-642-21735-7_26", series = "Lecture Notes in Computer Science", booktitle = "Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN), Part I", corerank = "B", abstract = "We present a {B}ayesian translational model for matching patterns in data sets which have neither co-occurring samples nor variables, but only a similar experiment design dividing the samples into two or more categories. The model estimates covariate effects related to this design and separates the factors that are shared across the data sets from those specific to one data set. The model is designed to find similarities in medical studies, where there is great need for methods for linking laboratory experiments with model organisms to studies of human diseases and new treatments.", volume = "6791", flags = "AIRC HIIT public copy", il = "no", year = "2011", internalpdf = "suvitaival11.pdf", unitcode = "T3060=99,U9014=1", impactfactor = "A4", pages = "209--216" }