PSB 2021 will continue to move forward with plans to be in Hawaii. We are monitoring the Covid-19 pandemic and will modify the plans if need be. We look forward to everyone’s participation.
PSB is offering eight workshops during the meeting (exact dates to be determined). These workshops were created to provide an opportunity for a gathering that will not be based on peer-reviewed papers included in the proceedings book. The workshops will consist of presentations by invited speakers. Abstract submissions for the workshops will be evaluated by the workshop co-chairs.
Each workshop has a chair who is responsible for organizing submissions. Please contact the specific session chair relevant to your interests for further information. Links on each of the session titles below lead to more detailed calls for participation.
- Bioinformatics of Corals
- Translational Bioinformatics
- Intersection of genomics, socioeconomic status and health outcome across race and ethnicity
- Making Tools that People Will Use: User-Centered Design in Computational Biology Research
- Packaging Biocomputing Software to Maximize Distribution and Reuse
- Raising the Stakeholders: Improving Patient Outcomes Through Interprofessional Collaborations in AI for Healthcare
- Establishing the Reliability of Algorithms in Biomedical Informatics
- Workshop on Social, Technical, and Ethical Challenges in Biomedical Data Privacy
A large amount of genomic, transcriptomic and other omics data from different species of reef building corals, the uni-cellular dinoflagellates, plus coral microbiome data (where corals have possibly the most complex microbiome yet discovered, consisting of over 20,000 different species), is becoming increasingly available for corals. This is a terrific opportunity for bioinformatics researchers and computational biologists to contribute to a timely, compelling and urgent investigation of critical factors that influence reef health and resilience. It is particularly relevant for this session to occur in Hawai'i given the abundance of and reliance on coral reefs in the region.
Contact: Lenore Cowen
Email: cowen at cs dot tufts dot edu
Translational bioinformatics (TBI) is a multi-disciplinary and rapidly emerging field of biomedical data sciences and informatics that includes the development of technologies that efficiently translate basic molecular, genetic, cellular, and clinical data into clinical products or health implications. TBI is a relatively young discipline that spans a wide spectrum from big data to comprehensive analytics to diagnostics and therapeutics. TBI involves applying novel methods to the storage, analysis, and interpretation of a massive volume of ‘omics and clinical data, and it bridges the gap between bench research and real-world applications to human health. Many health-related topics are increasingly falling within the scope of TBI, including rare and complex human disease, cancer, biomarkers, pharmacogenomics, drug repositioning, and clinical decision support systems.
Contact: Dokyoon Kim
Email: Dokyoon dot Kim at pennmedicine dot upenn dot edu
Health disparities include differences in the health status and/or health outcomes among population groups which may be identified by ethnicity, gender, sexual orientation, or age. Biocomputing can enhance the understanding of disparities in terms of lived health experiences, health outcomes, and issues involving social justice. The opportunities of using computational methods to better understand aspects of disparity among population groups will be addressed in this workshop.
Contact: William M. Southerland
Email: wsoutherland at howard dot edu
The goal of User-Centered Design (UCD) is to create a product that satisfies users needs, has an interface that is effective, and, in general, is a tool that people want to use. This workshop will be an overview of UCD as well as how it has been successfully applied to several computational biology tools. Attendees will leave with an understanding of common UCD practices and models of how they might apply them to their own tools.
Contact: Mary Goldman
Email: mary at soe dot ucsc dot edu
The majority of accepted papers in biocomputing describe new computational approaches to relevant biological problems, and while journals and conferences often require the availability of software and source code, there are limited resources available for trainees to maximize the distribution and use of their software within the scientific community. While the accepted standard is to make source code available for new approaches published work, the growing problem of system configuration issues, language and library version conflicts, and other implementation issues often impede the broad distribution and availability of software tools. There are a variety of solutions to these implementation issues, but the learning curve for applying these solutions is steep. In this tutorial for the Pacific Symposium of Biocomputing, we will demonstrate tools and approaches for packaging and distribution of published code.
Contact: William S. Bush
Email: wsb36 at case dot edu
Artificial intelligence (AI) and other computational and bioinformatic approaches have become a critical component of biomedical research. The wealth of available medical data and pertinent research questions have driven experts across many scientific fields to begin developing computational methods to drive innovation in medical research. However, AI in healthcare is often labelled as “disruptive”, a word simultaneously embracing its innovative nature, while warning against its turbulent impact on a broad range of health-care related disciplines. As a result, many healthcare stakeholders continue to be reserved, and even outright resistant, to AI advances for clinical outcomes.
Contact: Carly Bobak
Email: Carly.A.Bobak.GR at dartmouth dot edu
As rich data streams are accumulating across people and time, they provide a powerful opportunity to address limitations in our existing scientific knowledge and to overcome operational challenges in healthcare and life sciences. Yet the relative weighting of insights vs. methodologies in our current research ecosystem tends to skew the computational community away from algorithm evaluation and operationalization, resulting in well-reported proliferation of scientific outcomes of unknown reliability. Algorithm selection and use is hindered by several problems that persist across our field. One is the impact of the self-assessment bias, which can lead to mis-representations in the accuracy of research results. A second challenge is the impact of data context on algorithm performance. Biology and medicine are dynamic and heterogeneous. Data is collected under varying conditions. For algorithms, this means that performance is not universal -- and should be evaluated across a range of conditions. These issues are increasingly difficult as algorithms are trained and used on data collected outside of the research setting - where data collection is not well controlled and data access may be limited by privacy or proprietary reasons. This workshop will focus on approaches that are emerging across the researcher community to quantify the accuracy of algorithms and the reliability of their outputs.
Contact: Lara Mangravite
Email: lara dot mangravite at sagebionetworks dot org
With decreasing cost of biotechnology, the amount and the size of the available biomedical data have exponentially increased and become available to wider audiences. Hence, privacy of patients and study participants has recently emerged as one of the major foci of studies. Availability of genetic and health care information gives rise to privacy concerns such that people suffer dignitary harm when their data is used in ways they did not desire or intend, even if no concrete economic damage results. In this workshop, we propose a practical and interactive exploration of the technical and ethical frames that govern data sharing and use to advance human health from a privacy perspective. We will discuss the ethical and moral frames through which we can consider privacy, the existing regulations regarding privacy and what is on the horizon, and implementation of such ethical considerations for data with the new Common Rule. We will also discuss the approaches to ensuring privacy using technology, in which we will discuss the technologies that allow responsible use and sharing of data such as encryption and the quantification of privacy leakages in publicly available data through privacy attacks for better risk-assessment tools. We will end the workshop with a panel discussion. The mission is to bring together computational biologists, experimental biologists, computer scientists, ethicists, and policy and lawmakers to share ideas, discuss the challenges related to biological data and privacy and hopefully create collaborations.
Contact: Gamze Gursoy
Email: gamze dot gursoy at yale dot edu