Predictive modeling of gene expression regulation

Background In-depth analysis of regulation networks of genes aberrantly expressed in cancer is essential for better understanding tumors and identifying key genes that could be therapeutically targeted. Results We developed a quantitative analysis approach to investigate the main biological relationships among different regulatory elements and target genes; we applied it to Ovarian Serous Cystadenocarcinoma and 177 target genes belonging to three main pathways (DNA REPAIR, STEM CELLS and GLUCOSE METABOLISM) relevant for this tumor. Combining data from ENCODE and TCGA datasets, we built a predictive linear model for the regulation of each target gene, assessing the relationships between its expression, promoter methylation, expression of genes in the same or in the other pathways and of putative transcription factors. We proved the reliability and significance of our approach in a similar tumor type (basal-like Breast cancer) and using a different existing algorithm (ARACNe), and we obtained experimental confirmations on potentially interesting results. Conclusions The analysis of the proposed models allowed disclosing the relations between a gene and its related biological processes, the interconnections between the different gene sets, and the evaluation of the relevant regulatory elements at single gene level. This led to the identification of already known regulators and/or gene correlations and to unveil a set of still unknown and potentially interesting biological relationships for their pharmacological and clinical use.

Making kin

Thanks to next generation sequencing (NGS), we can now access ancient biological relationships, including ancestry and parentage, with a startling level of clarity. This has led to recentering of kinship within archaeological discourse. In this paper, we argue that blood and biology are key elements of kin-making only in so far as they are contextualized and made sense of through social relations. We argue that the conceptions of kinship that underpin archaeogenetic studies are the product of a particular historical and political context. Archaeology, with its focus on the material remains of the past, provides opportunities to examine how other forms of material and technological intervention (including ritual, exchange, and the sharing of food) facilitated the creation of kinship links not solely rooted in the human body. Here, we consider the extent to which the social salience of biological relationships identified through ancient DNA analysis can be addressed without imposing contemporary forms of familial structure and gender ideology onto the past.

Construction of a Physical Factor Resource for Exposome Informatics Research

Exposome research is focused on all the exposures individuals experience during their lifetime and how it shapes their health and development of disease. The chemical and biological aspects of the exposome are readily available in data formats. In comparison there is a lack of data frameworks available for physical factors (e.g. noise, lighting, electromagnetic fields) and their biological relationships which would allow a greater understanding of the contribution of the physical environment on disease development and burden. We present the construction of a prototype that captures knowledge on physical factors and their interactions with genes and diseases derived from the biomedical literature to reflect the physical exposome.

Biological Relationships

Weiss and Springer explain the many ways anthropologists determine biological relatedness; DNA, mitochondrial DNA, Y-chromosome DNA, metric and nonmetric cranial and dental traits are all types of data used to reconstruct who is related to whom. These methods have helped to answer how the Americas were peopled.