Dissecting spatio‐temporal protein networks driving human heart development and related disorders

Autor: Kasper Lage, Kjeld Møllgård, Steven Greenway, Hiroko Wakimoto, Joshua M Gorham, Christopher T Workman, Eske Bendsen, Niclas T Hansen, Olga Rigina, Francisco S Roque, Cornelia Wiese, Vincent M Christoffels, Amy E Roberts, Leslie B Smoot, William T Pu, Patricia K Donahoe, Niels Tommerup, Søren Brunak, Christine E Seidman, Jonathan G Seidman, Lars A Larsen

Publikováno v: Molecular Systems Biology, Vol 6, Iss 1, Pp 1-9 (2010)

Abstract Aberrant organ development is associated with a wide spectrum of disorders, from schizophrenia to congenital heart disease, but systems‐level insight into the underlying processes is very limited. Using heart morphogenesis as general model

Externí odkaz: https://doaj.org/article/a8fa2146859749fd8dbcf313b9364bb1

Using electronic patient records to discover disease correlations and stratify patient cohorts.

Autor: Francisco S Roque, Peter B Jensen, Henriette Schmock, Marlene Dalgaard, Massimo Andreatta, Thomas Hansen, Karen Søeby, Søren Bredkjær, Anders Juul, Thomas Werge, Lars J Jensen, Søren Brunak

Publikováno v: PLoS Computational Biology, Vol 7, Iss 8, p e1002141 (2011)

Electronic patient records remain a rather unexplored, but potentially rich data source for discovering correlations between diseases. We describe a general approach for gathering phenotypic descriptions of patients from medical records in a systemat

Externí odkaz: https://doaj.org/article/99ba46806dcc46edb876c08be452b359

ChemProt: a disease chemical biology database

Autor: Thomas Skøt Jensen, Alina Bora, Søren Brunak, Ramona Curpan, Sonny Kim Nielsen, Irene Kouskoumvekaki, Tudor I. Oprea, Karine Audouze, Olivier Taboureau, Nils Weinhold, Daniel Edsgärd, Francisco S. Roque

Publikováno v: Nucleic Acids Research
Taboureau, O, Nielsen, S K, Audouze, K M L, Weinhold, N, Edsgard, S D, Roque, F J S S A, Kouskoumvekaki, I, Bora, A, Curpan, R, Jensen, T S, Brunak, S & Oprea, T 2011, ' ChemProt: a disease chemical biology database ', Nucleic Acids Research, vol. 39, no. Issue Suppl. 1, pp. D367-372 . https://doi.org/10.1093/nar/gkq906

Systems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a1d936d15a4e80fed656ca2193ef7db
http://europepmc.org/articles/PMC3013776

GBA2 Mutations Cause a Marinesco-Sjögren-Like Syndrome: Genetic and Biochemical Studies

Autor: Wenche Telstad, Kristoffer Haugarvoll, Stefan Johansson, Helge Boman, Laurence A. Bindoff, Per M. Knappskog, Inge Jonassen, Ove Bruland, Bjørn Ivar Haukanes, Francisco S. Roque, Jan-Eric Månsson, Carlos E Rodriguez, Maria Blomqvist

Publikováno v: PLoS ONE
PLoS ONE, Vol 12, Iss 1, p e0169309 (2017)

Background: With the advent new sequencing technologies, we now have the tools to understand the phenotypic diversity and the common occurrence of phenocopies. We used these techniques to investigate two Norwegian families with an autosomal recessive

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a5b2b1594d3a932b1b4ff00a4fdb9e8
https://doi.org/10.1371/journal.pone.0169309

Using electronic patient records to discover disease correlations and stratify patient cohorts

Autor: Marlene Danner Dalgaard, Francisco S. Roque, Thomas Hansen, Søren Brunak, Søren Bredkjær, Lars Juhl Jensen, Massimo Andreatta, Peter Bjødstrup Jensen, Thomas Werge, Karen Søeby, Henriette Schmock, Anders Juul

Publikováno v: PLoS Computational Biology, Vol 7, Iss 8, p e1002141 (2011)
Roque, F S, Jensen, P B, Schmock, H, Dalgaard, M, Andreatta, M, Hansen, T, Søeby, K, Bredkjaer, S, Juul, A, Werge, T, Jensen, L J & Brunak, S 2011, ' Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts ', P L o S Computational Biology (Online), vol. 7, no. 8 . https://doi.org/10.1371/journal.pcbi.1002141
PLoS Computational Biology

Electronic patient records remain a rather unexplored, but potentially rich data source for discovering correlations between diseases. We describe a general approach for gathering phenotypic descriptions of patients from medical records in a systemat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27b6a2ebb3fd6a80b7f431058e62d17e
https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21901084/?tool=EBI