scispace - formally typeset
H

Hans A. Kestler

Researcher at University of Ulm

Publications -  351
Citations -  11671

Hans A. Kestler is an academic researcher from University of Ulm. The author has contributed to research in topics: Medicine & QRS complex. The author has an hindex of 50, co-authored 322 publications receiving 9994 citations. Previous affiliations of Hans A. Kestler include National Institutes of Health & École Normale Supérieure.

Papers
More filters
Journal ArticleDOI

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

Robert A. Scott, +216 more
- 01 Nov 2017 - 
TL;DR: This article conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel.
Journal ArticleDOI

Sequelae of acute myocardial infarction regarding cardiac structure and function and their prognostic significance as assessed by magnetic resonance imaging.

TL;DR: MRI is a highly sensitive and reliable tool to detect morphologic and functional sequelae of AMI providing baseline MRI parameters with relevant predictive power for LV adverse remodelling and occurrence of MACE.
Journal ArticleDOI

Three learning phases for radial-basis-function networks

TL;DR: It can be observed that the performance of RBF classifiers trained with two-phase learning can be improved through a third backpropagation-like training phase of the RBF network, adapting the whole set of parameters (RBF centers, scaling parameters, and output layer weights) simultaneously.
Journal ArticleDOI

MYC stimulates EZH2 expression by repression of its negative regulator miR-26a.

TL;DR: It is shown that ectopic expression of miR-26a influenced cell cycle progression by targeting the bona fide oncogene EZH2, a Polycomb protein and global regulator of gene expression yet unknown to be regulated by miRNAs, thereby vitally contributing to MYC-induced lymphomagenesis.
Journal ArticleDOI

BoolNet—an R package for generation, reconstruction and analysis of Boolean networks

TL;DR: BoolNet efficiently integrates methods for synchronous, asynchronous and probabilistic BNs, and includes reconstructing networks from time series, generating random networks, robustness analysis via perturbation, Markov chain simulations, and identification and visualization of attractors.