Towards Novel Nonparametric Statistical Methods and Bioinformatics Tools for Clinical and Translational Sciences

As the field of functional genetics and genomics is beginning to mature, we become confronted with new challenges. The constant drop in price for sequencing and gene expression profiling as well as the increasing number of genetic and genomic variables that can be measured makes it feasible to address more complex questions. The success with rare diseases caused by single loci or genes has provided us with a proof-of-concept that new therapies can be developed based on functional genomics and genetics. Common diseases, however, typically involve genetic epistasis, genomic pathways, and proteomic pattern. Moreover, to better understand the underlying biologi-cal systems, we often need to integrate information from several of these sources. Thus, as the field of clinical research moves toward complex diseases, the demand for modern data base systems and advanced statistical methods increases. The traditional statistical methods implemented in most of the bioinformatics tools currently used in the novel field of genetics and functional genomics are based on the linear model and, thus, have shortcomings when applied to nonlinear biological systems. The previous work on partially ordered data (Wittkowski 1988; 1992), when combined with theoretical results (Hoeffding 1948) and computational strategies (Deuchler 1914) has opened a new field of nonparametric statistics. With grid technology, new tools are now feasible when screening for interactions between genetics (Wittkowski, Liu 2002) and functional genomics (Wittkowski, Lee 2004). Having more complex study designs and more specific methods available increases the demand for decision support when selecting appropriate bioinformatics tools. With the advent of rapid prototyping systems for Web based database application, we have recently begun to complement previous work on knowledge based systems with graphical Web-based tools for acquisition of DESIGN and MODEL knowledge.Biostatistics Bioinformatics NIH NCRR ROADMAP

Increasing confidence and changing behaviors in primary care providers engaged in genetic counselling.

BackgroundScreening and counseling for genetic conditions is an increasingly important part of primary care practice, particularly given the paucity of genetic counselors in the United States. However, primary care physicians (PCPs) often have an inadequate understanding of evidence-based screening; communication approaches that encourage shared decision-making; ethical, legal, and social implication (ELSI) issues related to screening for genetic mutations; and the basics of clinical genetics. This study explored whether an interactive, web-based genetics curriculum directed at PCPs in non-academic primary care settings was superior at changing practice knowledge, attitudes, and behaviors when compared to a traditional educational approach, particularly when discussing common genetic conditions.MethodsOne hundred twenty one PCPs in California and Pennsylvania physician practices were randomized to either an Intervention Group (IG) or Control Group (CG). IG physicians completed a 6 h interactive web-based curriculum covering communication skills, basics of genetic testing, risk assessment, ELSI issues and practice behaviors. CG physicians were provided with a traditional approach to Continuing Medical Education (CME) (clinical review articles) offering equivalent information.ResultsPCPs in the Intervention Group showed greater increases in knowledge compared to the Control Group. Intervention PCPs were also more satisfied with the educational materials, and more confident in their genetics knowledge and skills compared to those receiving traditional CME materials. Intervention PCPs felt that the web-based curriculum covered medical management, genetics, and ELSI issues significantly better than did the Control Group, and in comparison with traditional curricula. The Intervention Group felt the online tools offered several advantages, and engaged in better shared decision making with standardized patients, however, there was no difference in behavior change between groups with regard to increases in ELSI discussions between PCPs and patients.ConclusionWhile our intervention was deemed more enjoyable, demonstrated significant factual learning and retention, and increased shared decision making practices, there were few differences in behavior changes around ELSI discussions. Unfortunately, barriers to implementing behavior change in clinical genetics is not unique to our intervention. Perhaps the missing element is that busy physicians need systems-level support to engage in meaningful discussions around genetics issues. The next step in promoting active engagement between doctors and patients may be to put into place the tools needed for PCPs to easily access the materials they need at the point-of-care to engage in joint discussions around clinical genetics

New Statistical Paradigms Leading to Web-Based Tools for Clinical/Translational Science

As the field of functional genetics and genomics is beginning to mature, we become confronted with new challenges. The constant drop in price for sequencing and gene expression profiling as well as the increasing number of genetic and genomic variables that can be measured makes it feasible to address more complex questions. The success with rare diseases caused by single loci or genes has provided us with a proof-of-concept that new therapies can be developed based on functional genomics and genetics. Common diseases, however, typically involve genetic epistasis, genomic pathways, and proteomic pattern. Moreover, to better understand the underlying biologi-cal systems, we often need to integrate information from several of these sources. Thus, as the field of clinical research moves toward complex diseases, the demand for modern data base systems and advanced statistical methods increases. The traditional statistical methods implemented in most of the bioinformatics tools currently used in the novel field of genetics and functional genomics are based on the linear model and, thus, have shortcomings when applied to nonlinear biological systems. The previous work on partially ordered data (Wittkowski 1988; 1992), when combined with theoretical results (Hoeffding 1948) and computational strategies (Deuchler 1914) has opened a new field of nonparametric statistics. With grid technology, new tools are now feasible when screening for interactions between genetics (Wittkowski, Liu 2002) and functional genomics (Wittkowski, Lee 2004). Having more complex study designs and more specific methods available increases the demand for decision support when selecting appropriate bioinformatics tools. With the advent of rapid prototyping systems for Web based database application, we have recently begun to complement previous work on knowledge based systems with graphical Web-based tools for acquisition of DESIGN and MODEL knowledge

Single-gene influences on brain and behavior

As traditional behavioral genetics analysis merges with neurogenetics, the field of neurobehavioral genetics, focusing on single-gene effects, comes into being. New biotechnology has greatly accelerated gene discovery and the study of gene function in relation to brain and behavior. More than 7,000 genes in mice and 10,000 in humans have now been documented, and extensive information about the genetics of several species is readily available on the World Wide Web. Based on knowledge of the DNA sequence of a gene, a targeted mutation with the capacity to disable it can be created. These knockouts--also called null mutants-- are employed in the study of a wide range of phenotypes, including learning and memory, appetite and obesity, and circadian rhythms. The era of examining single-gene effects from a reductionistic perspective is waning, and research with interacting arrays of genes in various environmental contexts is demonstrating a need for systems-oriented theory

Towards Novel Nonparametric Statistical Methods and Bioinformatics Tools for Clinical and Translational Sciences

As the field of functional genetics and genomics is beginning to mature, we become confronted with new challenges. The constant drop in price for sequencing and gene expression profiling as well as the increasing number of genetic and genomic variables that can be measured makes it feasible to address more complex questions. The success with rare diseases caused by single loci or genes has provided us with a proof-of-concept that new therapies can be developed based on functional genomics and genetics. Common diseases, however, typically involve genetic epistasis, genomic pathways, and proteomic pattern. Moreover, to better understand the underlying biologi-cal systems, we often need to integrate information from several of these sources. Thus, as the field of clinical research moves toward complex diseases, the demand for modern data base systems and advanced statistical methods increases. The traditional statistical methods implemented in most of the bioinformatics tools currently used in the novel field of genetics and functional genomics are based on the linear model and, thus, have shortcomings when applied to nonlinear biological systems. The previous work on partially ordered data (Wittkowski 1988; 1992), when combined with theoretical results (Hoeffding 1948) and computational strategies (Deuchler 1914) has opened a new field of nonparametric statistics. With grid technology, new tools are now feasible when screening for interactions between genetics (Wittkowski, Liu 2002) and functional genomics (Wittkowski, Lee 2004). Having more complex study designs and more specific methods available increases the demand for decision support when selecting appropriate bioinformatics tools. With the advent of rapid prototyping systems for Web based database application, we have recently begun to complement previous work on knowledge based systems with graphical Web-based tools for acquisition of DESIGN and MODEL knowledge

Understanding of BRCA VUS genetic results by breast cancer specialists.

BACKGROUND: Mainstreaming genetic medicine, increased media coverage and clinical trials for BRCA mutation carriers are leading oncologists into more patient discussions about BRCA genetic testing. BRCA variants of uncertain significance (VUS) occur in 10-20% of tests. VUS detection introduces additional uncertainty for patient and potentially clinician. We aimed to explore the ability of breast cancer specialists (BCS) in the UK to correctly respond to a VUS report. METHODS: A survey sent to 800 UK BCS collected demographics data, VUS general knowledge and interpretation and communication based on two genetics reports. A separate survey of UK clinical geneticists collected demographics data, laboratory reporting practice and methods used to clarify VUS pathogenicity including classification systems. RESULTS: Of the 155 BCS (22.5%) who completed the survey, 12% reported no genetics training. Ninety five percent referred patients for BRCA genetic tests, 71% felt unsure about the clinical implications of the test reports presented here. A VUS report from a patient with a positive family history was interpreted and theoretically communicated correctly by 94% but when presented with a different VUS report with no management guidance and negative family history, 39% did not know how to communicate this result to the patient. Geneticists reported multiple VUS classification systems; the most commonly used was word-based in 32%. CONCLUSIONS: A consistent and standardised format to report particularly VUS results across all diagnostic laboratories plus additional training of UK BCS will be necessary for effective mainstreaming of BRCA testing to the oncology clinic

PlantBot Genetics Presents: The Moth Project

PlantBot Genetics Inc. presents an engaging overview of second shift pollinators such as the moth, along with recent advances in self-pollinating robo-plants. The Moth Project highlights inspired responses to the decline of the honeybee and the hope that Moths and PlantBots will step in and save the day. As consumers, we no longer know the real price of our food. Present food distribution systems are so complicated that it is unrealistic to expect consumers will make responsible choices based on the knowledge at hand. We encourage people to think more about their food, where it comes from, and where it may be going. PlantBot Genetics shares the remote control in the ArtLab, releases robotic plants, commandeers public spaces, offers mothing events, and plants a night blooming community garden. Whether it be a street, museum, or gallery based event, our goal is to inspire people to question the food they eat and how it got there in an entertaining and artistic way. Having an out of gallery experience is often more memorable and can speak to a much wider audience. Our street tactics bring art and education into a community despite the level of support for healthy food or art culture in that particular location.https://digitalcommons.augustana.edu/artmuseumexhibitions2015-16/1002/thumbnail.jp

Innovation sustainability in challenging health-care contexts : embedding clinically led change in routine practice

The need for organizational innovation as a means of improving health-care quality and containing costs is widely recognized, but while a growing body of research has improved knowledge of implementation, very little has considered the challenges involved in sustaining change – especially organizational change led ‘bottom-up’ by frontline clinicians. This study addresses this lacuna, taking a longitudinal, qualitative case-study approach to understanding the paths to sustainability of four organizational innovations. It highlights the importance of the interaction between organizational context, nature of the innovation and strategies deployed in achieving sustainability. It discusses how positional influence of service leads, complexity of innovation, networks of support, embedding in existing systems, and proactive responses to changing circumstances can interact to sustain change. In the absence of cast-iron evidence of effectiveness, wider notions of value may be successfully invoked to sustain innovation. Sustainability requires continuing effort through time, rather than representing a final state to be achieved. Our study offers new insights into the process of sustainability of organizational change, and elucidates the complement of strategies needed to make bottom-up change last in challenging contexts replete with competing priorities