https://www.selleckchem.com/products/almorexant-hcl.html Congenital hypogonadotropic hypogonadism (CHH) is caused by dysfunction of hypothalamic gonadotropic-releasing hormone (GnRH) axis. The condition is both clinically and genetically heterogeneous with more than 40 genes implicated in pathogenesis. The goal of the present study was to identify causative mutations in CHH individuals employing 2 step procedure with a targeted NGS panel as first-line diagnostics and subsequently whole exome sequencing in unsolved cases. Known or novel potentially deleterious variants were found in 28 out of 47 tested CHH patients. Molecular diagnosis was reached in 19/47 CHH cases. In 13 cases monogenic variants were identified in ANOS1, FGFR1, GNRHR, CHD7, SOX10, and PROKR2, while 6 patients showed digenic or trigenic inheritance patterns. The achieved diagnostic rate was comparable to other studies on genetics of CHH. By evaluating and reporting more patients with CHH we make progress in unravelling its genetic complexity and move a step closer to personalised medicine.Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovarian cancer patients can facilitate the therapeutics evaluation and treatment decision making. Multi-scale multi-omics data such as gene expression, DNA methylation, miRNA expression, and copy number variations can provide insights on personalized survival. However, how to effectively integrate multi-omics data remains a challenging task. In this paper, we develop multi-omics integration methods to improve the prediction of overall survival for breast cancer and ovarian cancer patients. Because multi-omics data for the same patient jointly impact the survival of cancer patients, features from different -omics modality are related and can be modeled by either association or causal relationship (e.g., pathways). By extracting these relationships among modalities, we can