Local Independence Testing for Point Processes.

Constraint-based causal structure learning for point processes require empirical tests of local independence. Existing tests require strong model assumptions, e.g.

FANCD2 binding identifies conserved fragile sites at large transcribed genes in avian cells.

Common Chromosomal Fragile Sites (CFSs) are specific genomic regions prone to form breaks on metaphase chromosomes in response to replication stress. Moreover, CFSs are mutational hotspots in cancer genomes, showing that the mutational mechanisms that operate at CFSs are highly active in cancer cells. Orthologs of human CFSs are found in a number of other mammals, but the extent of CFS conservation beyond the mammalian lineage is unclear.

Survival prognosis and variable selection: A case study for metastatic castrate resistant prostate cancer patients.

Survival prognosis is challenging, and accurate prediction of individual survival times is often very difficult. Better statistical methodology and more data can help improve the prognostic models, but it is important that methods and data usages are evaluated properly. The Prostate Cancer DREAM Challenge offered a framework for training and blinded validation of prognostic models using a large and rich dataset on patients diagnosed with metastatic castrate resistant prostate cancer.

Development and validation of a microRNA based diagnostic assay for primary tumor site classification of liver core biopsies.

Identification of the primary tumor site in patients with metastatic cancer is clinically important, but remains a challenge. Hence, efforts have been made towards establishing new diagnostic tools. Molecular profiling is a promising diagnostic approach, but tissue heterogeneity and inadequacy may negatively affect the accuracy and usability of molecular classifiers.

Modeling tissue contamination to improve molecular identification of the primary tumor site of metastases.

Motivation: Contamination of a cancer tissue by the surrounding benign (non-cancerous) tissue is a concern for molecular cancer diagnostics. This is because an observed molecular signature will be distorted by the surrounding benign tissue, possibly leading to an incorrect diagnosis. One example is molecular identification of the primary tumor site of metastases because biopsies of metastases typically contain a significant amount of benign tissue.

Statistical models for local occurrences of RNA structures.

We develop in this article the necessary statistical theory for computing, for instance, E-values when searching long sequences for the occurrences of local RNA-structures. We show in particular how the theory can be used for estimating scoring parameters with the purpose of optimizing the discriminative performance of the algorithm. The results are implemented in the program StemSearch, which can search for stem loop structures that are formed by, for example, micro RNA precursors.