Abstract

Abstract

Abstract
Recent years have witnessed an increased interest, by competition agencies, in assessing the competitive effects of partial acquisitions. We propose a generalization of the two most traditional indicators used to screen unilateral anti-competitive effects - the HerfindahlHirschman Index and the Gross Up- ward Price Pressure Index - to partial horizontal acquisition settings. The proposed generalized indicators are endogenously derived under a probabilistic voting model in which the manager of each firm is elected in a shareholder assembly between two potential candidates who seek to obtain utility from an exogenous rent associated with corporate office. The model (i) can cope with settings involving all types of owners and rights: owners that can be internal to the industry (rival firms) and external to the industry; and rights that can capture financial and corporate control interests, can be direct and indirect, can be partial or full, (ii) yields an endogenous measure of the owners ultimate corporate control rights, and (iii) can also be used - in case the potential acquisition is inferred to likely enhance market power - to devise divestiture structural remedies. We also provide an empirical application of the two proposed generalized indicators to several acquisitions in the wet shaving industry, with the objective of providing practitioners with a step-by-step illustration of how to compute them in antitrust cases.

Abstract

Abstract
Post-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates. By comparing ante-and postmortem blood samples, we identify the cascade of transcriptional events triggered by death of the organism. These events do not appear to simply reflect stochastic variation resulting from mRNA degradation, but active and ongoing regulation of transcription. Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.

Abstract
Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important bioinformatics problems, putting forward the best algorithms and showing how to implement them. The book focuses on the use of the Python programming language and its algorithms, which is quickly becoming the most popular language in the bioinformatics field. Readers will find the tools they need to improve their knowledge and skills with regard to algorithm development and implementation, and will also uncover prototypes of bioinformatics applications that demonstrate the main principles underlying real world applications.