Object-oriented Bayesian networks for evaluating DIP-STR profiling results from unbalanced DNA mixtures.

The genetic characterization of unbalanced mixed stains remains an important area where improvement is imperative. In fact, with current methods for DNA analysis (Polymerase Chain Reaction with the SGM Plus™ multiplex kit), it is generally not possible to obtain a conventional autosomal DNA profile of the minor contributor if the ratio between the two contributors in a mixture is smaller than 1:10. This is a consequence of the fact that the major contributor's profile 'masks' that of the minor contributor. Besides known remedies to this problem, such as Y-STR analysis, a new compound genetic marker that consists of a Deletion/Insertion Polymorphism (DIP), linked to a Short Tandem Repeat (STR) polymorphism, has recently been developed and proposed elsewhere in literature [1]. The present paper reports on the derivation of an approach for the probabilistic evaluation of DIP-STR profiling results obtained from unbalanced DNA mixtures. The procedure is based on object-oriented Bayesian networks (OOBNs) and uses the likelihood ratio as an expression of the probative value. OOBNs are retained in this paper because they allow one to provide a clear description of the genotypic configuration observed for the mixed stain as well as for the various potential contributors (e.g., victim and suspect). These models also allow one to depict the assumed relevance relationships and perform the necessary probabilistic computations.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Using graphical probability analysis (Bayes Nets) to evaluate a conditional DNA inclusion

This paper discusses the analysis of cases in which the inclusion or exclusion of a particular suspect, as a possible contributor to a DNA mixture, depends on the value of a variable (the number of contributors) that cannot be determined with certainty. It offers alternative ways to deal with such cases, including sensitivity analysis and object-oriented Bayesian networks, that separate uncertainty about the inclusion of the suspect from uncertainty about other variables. The paper presents a case study in which the value of DNA evidence varies radically depending on the number of contributors to a DNA mixture: if there are two contributors, the suspect is excluded; if there are three or more, the suspect is included; but the number of contributors cannot be determined with certainty. It shows how an object-oriented Bayesian network can accommodate and integrate varying perspectives on the unknown variable and how it can reduce the potential for bias by directing attention to relevant considerations and distinguishing different sources of uncertainty. It also discusses the challenge of presenting such evidence to lay audiences.

Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'.

Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models ( e. g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.Results: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.Conclusion: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

MyHits: improvements to an interactive resource for analyzing protein sequences.

The MyHits web site (http://myhits.isb-sib.ch) is an integrated service dedicated to the analysis of protein sequences. Since its first description in 2004, both the user interface and the back end of the server were improved. A number of tools (e.g. MAFFT, Jacop, Dotlet, Jalview, ESTScan) were added or updated to improve the usability of the service. The MySQL schema and its associated API were revamped and the database engine (HitKeeper) was separated from the web interface. This paper summarizes the current status of the server, with an emphasis on the new services.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

EuroPhenome: a repository for high-throughput mouse phenotyping data.

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.

Evaluating fear of falling among community-dwelling older people: A qualitative pattern model based on the experience of falls

This research was conducted in the context of the project IRIS 8A Health and Society (2002-2008) and financially supported by the University of Lausanne. It was aomed at developping a model based on the elder people's experience and allowed us to develop a "Portrait evaluation" of fear of falling using their examples and words. It is a very simple evaluation, which can be used by professionals, but by the elder people themselves. The "Portrait evaluation" and the user's guide are on free access, but we would very much approciate to know whether other people or scientists have used it and collect their comments. (contact: Chantal.Piot-Ziegler@unil.ch)The purpose of this study is to create a model grounded in the elderly people's experience allowing the development of an original instrument to evaluate FOF.In a previous study, 58 semi-structured interviews were conducted with community-dwelling elderly people. The qualitative thematic analysis showed that fear of falling was defined through the functional, social and psychological long-term consequences of falls (Piot-Ziegler et al., 2007).In order to reveal patterns in the expression of fear of falling, an original qualitative thematic pattern analysis (QUAlitative Pattern Analysis - QUAPA) is developed and applied on these interviews.The results of this analysis show an internal coherence across the three dimensions (functional, social and psychological). Four different patterns are found, corresponding to four degrees of fear of falling. They are formalized in a fear of falling intensity model.This model leads to a portrait-evaluation for fallers and non-fallers. The evaluation must be confronted to large samples of elderly people, living in different environments. It presents an original alternative to the concept of self-efficacy to evaluate fear of falling in older people.The model of FOF presented in this article is grounded on elderly people's experience. It gives an experiential description of the three dimensions constitutive of FOF and of their evolution as fear increases, and defines an evaluation tool using situations and wordings based on the elderly people's discourse.

quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation.

quantiNemo is an individual-based, genetically explicit stochastic simulation program. It was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits with varying architectures in structured populations connected by migration and located in a heterogeneous habitat. quantiNemo is highly flexible at various levels: population, selection, trait(s) architecture, genetic map for QTL and/or markers, environment, demography, mating system, etc. quantiNemo is coded in C++ using an object-oriented approach and runs on any computer platform. Availability: Executables for several platforms, user's manual, and source code are freely available under the GNU General Public License at http://www2.unil.ch/popgen/softwares/quantinemo.

Donor's and organ representations in liver, kidney, heart and lung transplantation : a qualitative longitudinal study

Purpose: Organ transplantation is a biological and psychological challenge and graft acceptance is an important achievement for patients. Patients' concerns toward the deceased donor and the organ may contribute to this process. Method: Forty-seven patients involved in heart (N=9), liver (N=8), lung (N=14) and kidney (N=16) transplantation participated in IRB-approved longitudinal semi-structured interviews: (T1) registered on the waiting-list, (T2) six months and (T3) twelve months after transplantation. Qualitative pattern analysis (QUAPA) was carried out on the verbatim transcripts and concerns about the donor and the organ were then analysed. Results: - Donor's representation: At T1, patients were reluctant to talk about the donor: 27% expressed culpability and 19% accepted the clause of anonymity. At T2, intense emotions were associated with the reminiscing about the donor and 45% highlighted the generosity of his/her act. In addition, heart, lung and kidney recipients were concerned about the donor's identity: 42% challenged the clause of anonymity. Liver recipients complained about anonymity, but could nevertheless cope with it. At T3, 47% of heart, lung and kidney recipients thought daily of the donor and 33% were still looking for information about him/her. Liver recipients rarely have thoughts about the donor. - Organ representation: At T1, organ descriptions were biomedical (49% of the interviewees) and more rarely, mainly heart candidates, referred to the symbolic meaning of the organ. After transplantation (T2-T3), function was underlined. Acceptance and organ integration were associated with post-operative outcomes (23%) and psychological well-being (45%). Some patients (32%) inferred the donor's personality from the organ quality and felt privileged having received an organ in such a good state. Conclusion: Donor's representations should be explored during the transplantation process as they play an important role in the psychological acceptance of the graft.

A novel tool to analyze MRI recurrence patterns in glioblastoma.

At least 10% of glioblastoma relapses occur at distant and even contralateral locations. This disseminated growth limits surgical intervention and contributes to neurological morbidity. Preclinical data pointed toward a role for temozolomide (TMZ) in reducing radiotherapy-induced glioma cell invasiveness. Our objective was to develop and validate a new analysis tool of MRI data to examine the clinical recurrence pattern of glioblastomas. MRIcro software was used to map the location and extent of initial preoperative and recurrent tumors on MRI of 63 patients in the European Organisation for Research and Treatment of Cancer (EORTC) 26981/22981/National Cancer Institute of Canada (NCIC) CE.3 study into the same stereotaxic space. This allowed us to examine changes of site and distance between the initial and the recurrent tumor on the group level. Thirty of the 63 patients were treated using radiotherapy, while the other patients completed a radiotherapy-plus-TMZ treatment. Baseline characteristics (median age, KPS) and outcome data (progression-free survival, overall survival) of the patients included in this analysis resemble those of the general study cohort. The patient groups did not differ in the promoter methylation status of methyl guanine methyltransferase (MGMT). Overall frequency of distant recurrences was 20%. Analysis of recurrence patterns revealed no difference between the groups in the size of the recurrent tumor or in the differential effect on the distance of the recurrences from the preoperative tumor location. The data show the feasibility of groupwise recurrence pattern analysis. An effect of TMZ treatment on the recurrence pattern in the EORTC 26981/22981/NCIC CE.3 study could not be demonstrated.

Animal dispersal modelling: handling landscape features and related animal choices

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path.

Existential values transformation in all organ transplantation: A qualitative prospective study.

Organ transplantation offers a treatment of choice for patients suffering from end stage illnesses. The aim of this IRB approved prospective qualitative study was to analyze patients’ psychological concerns from their inclusion on the waiting list for first organ transplantation (TX) (T1; N=71; kidney, K=30; liver, Li=11; lung, Lu=15; heart, H=15) and six months after TX (T2; N=49; K=15; Li=10; Lu=14; H=10). Semi-structured interviews were conducted at home or in a place selected by patients. Qualitative pattern analysis (QUAPA) of the verbatim transcriptions was applied. T1 (K) Patients maintained an apparent normality (87%), building emotional protection (23%), and developing a fatalist attitude towards life (43%). (Li) Physical limits were set to spare energy until TX (73%). Illness led to reevaluation of life values (66%). (Lu) Physical and psychological self-protection was prioritized when health declined (67%). Modified life values, fatalism (33%) and spirituality (27 %) were mentioned. (H) Patients husbanded physical (80%) and psychological (67%) resources and self-protection. Modified life values and fatalist attitude towards life were reported (40%). T2 (K) New perspective on life was described, with increase of empathy towards others (20%). (Li) Positive identity and life values modifications (60%), greater openness towards others, closeness to significant ones (30%) and a more self-centered attitude (30%) prioritizing the essential (20%) were reported. Lack of respect of life values generated anger (40%). (Lu) Setting existential priorities and increase in spirituality (64%), along with the development of new life values, greater openness to others (57%) and closeness to significant ones (21%) were underlined. Lack of respect of human values induced negative feelings (36%). Self-centered attitudes, setting limits to other people were mentioned (29%). (H) Change in life values with setting life priorities was reported (70%) with increase in spirituality, and the lack of respect of life values generated anger (50%). Self-centered attitudes were reported (60%). TX not only comes with positive physical benefits, but also with positive existential values and psychological transformation, and the development of a more altruistic attitude and humanistic values.