How Much Does It Cost? Optimization of Costs in Sequence Analysis of Social Science Data

One major methodological problem in analysis of sequence data is the determination of costs from which distances between sequences are derived. Although this problem is currently not optimally dealt with in the social sciences, it has some similarity with problems that have been solved in bioinformatics for three decades. In this article, the authors propose an optimization of substitution and deletion/insertion costs based on computational methods. The authors provide an empirical way of determining costs for cases, frequent in the social sciences, in which theory does not clearly promote one cost scheme over another. Using three distinct data sets, the authors tested the distances and cluster solutions produced by the new cost scheme in comparison with solutions based on cost schemes associated with other research strategies. The proposed method performs well compared with other cost-setting strategies, while it alleviates the justification problem of cost schemes.

Supporting interdisciplinary case studies: development and implementation of a joint learning environment for students in forensic science and criminal law

Scientific reporting and communication is a challenging topic for which traditional study programs do not offer structured learning activities on a regular basis. This paper reports on the development and implementation of a web application and associated learning activities that intend to raise the awareness of reporting and communication issues among students in forensic science and law. The project covers interdisciplinary case studies based on a library of written reports about forensic examinations. Special features of the web framework, in particular a report annotation tool, support the design of various individual and group learning activities that focus on the development of knowledge and competence in dealing with reporting and communication challenges in the students' future areas of professional activity.

Bridging basic science and clinical research - The EASL Monothematic Conference on Translational Research in Viral Hepatitis.

The EASL Monothematic Conference on Translational Research in Viral Hepatitis brought together a group of leading scientists and clinicians working on both, basic and clinical aspects of viral hepatitis, thereby building bridges from bench to bedside. This report recapitulates the presentations and discussions at the conference held in Lyon, France on November 29-30, 2013. In recent years, great advances have been made in the field of viral hepatitis, particularly in hepatitis C virus (HCV) infection. The identification of IL28B genetic polymorphisms as a major determinant for spontaneous and treatment-induced HCV clearance was a seminal discovery. Currently, hepatologists are at the doorstep of even greater advances, with the advent of a wealth of directly acting antivirals (DAAs) against HCV. Indeed, promising results have accumulated over the last months and few years, showing sustained virological response (SVR) rates of up to 100% with interferon-free DAA combination therapies. Thus, less than 25years after its identification, HCV infection may soon be curable in the vast majority of patients, highlighting the great success of HCV research over the last decades. However, viral hepatitis and its clinical complications such as liver cirrhosis and hepatocellular carcinoma (HCC) remain major global challenges. New therapeutic strategies to tackle hepatitis B virus (HBV) and hepatitis D virus (HDV) infection are needed, as current therapies have undeniable limitations. Nucleoside/nucleotide analogues (NUC) can efficiently control HBV replication and reduce or even reverse liver damage. However, these drugs have to be given for indefinite periods in most patients to maintain virological and biochemical responses. Although sustained responses off treatment can be achieved by treatment with (pegylated) interferon-α, only about 10-30% of patients effectively resolve chronic hepatitis B. It was the goal of this conference to review the progress made over the last years in chronic viral hepatitis research and to identify key questions that need to be addressed in order to close the gap between basic and clinical research and to develop novel preventive and treatment approaches for this most common cause of liver cirrhosis and HCC.

Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

Drawbacks in the scientification of forensic science

This letter to the Editor comments on the article On the limitations of probability in conceptualizing pattern matches in forensic science by P. T. Jayaprakash (Forensic Science International