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correspondence tions (omitting the time stamps). We used interventional data on steady-state gene expression levels of known single-gene knockout experiments as the gold standard for determining the causal effects. We applied IDA, as well as Lasso and Elastic-net, to the observational datasets and evaluated how well the resulting top q predicted effects (q… (More)

- Markus Kalisch, Peter Bühlmann
- Journal of Machine Learning Research
- 2007

We consider the PC-algorithm ([13]) for estimating the skeleton of a very high-dimensional acyclic directed graph (DAG) with corresponding Gaussian distribution. The PC-algorithm is computationally feasible for sparse problems with many nodes, i.e. variables, and it has the attractive property to automatically achieve high computational efficiency as a… (More)

We assume that we have observational data, generated from an unknown underlying directed acyclic graph (DAG) model. A DAG is typically not identifiable from observational data, but it is possible to consistently estimate the equivalence class of a DAG. Moreover, for any given DAG, causal effects can be estimated using intervention calculus. In this paper,… (More)

The pcalg package for R (R Development Core Team (2010)) can be used for the following two purposes: Causal structure learning and estimation of causal effects from observational data. In this document, we give a brief overview of the methodology, and demonstrate the package's functionality in both toy examples and applications.

We consider the problem of learning causal information between random variables in directed acyclic graphs (DAGs) when allowing arbitrarily many latent and selection variables. The FCI (Fast Causal Inference) algorithm has been explicitly designed to infer conditional independence and causal information in such settings. However, FCI is computationally… (More)

- Marloes H Maathuis, Diego Colombo, Markus Kalisch, Peter Bühlmann
- Nature methods
- 2010

Supplementary Figure 1 Comparing IDA, Lasso and Elastic-net on the five DREAM4 networks of size 10 with multifactorial data. Supplementary Table 1 Comparing IDA, Lasso and Elastic-net to random guessing on the Hughes et al. data. Supplementary Table 2 Comparing IDA, Lasso and Elastic-net to random guessing on the five DREAM4 networks of size 10, using the… (More)

- Daniel Max Weber, Markus A Landolt, Rita Gobet, Markus Kalisch, Norma K Greeff
- The Journal of urology
- 2013

PURPOSE
Studies of the outcome of hypospadias repair must document quality, including assessment of complications and appraisal of appearance. To our knowledge the Pediatric Penile Perception Score is the first validated instrument for the outcome assessment of hypospadias repair in prepubertal males by surgeons and patients. We validated the instrument for… (More)

We assume that we have observational data generated from an unknown underlying directed acyclic graph (DAG) model. A DAG is typically not identifiable from observational data, but it is possible to consistently estimate the equivalence class of a DAG. Moreover, for any given DAG, causal effects can be estimated using intervention calculus. In this paper, we… (More)

- Markus Kalisch, Bernd AG Fellinghauer, +4 authors Gerold Stucki
- BMC medical research methodology
- 2010

BACKGROUND
Functioning and disability are universal human experiences. However, our current understanding of functioning from a comprehensive perspective is limited. The development of the International Classification of Functioning, Disability and Health (ICF) on the one hand and recent developments in graphical modeling on the other hand might be combined… (More)