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Session Type: Innovative Topics
Bridging Topic III: Management for Scientists, Part 1: Core Business & Graduate Education PartnershipManagement for Scientists is a unique educational collaboration between core facilities and the Vanderbilt University career development office for biomedical trainees. This twelve-week course targets both trainees and core personnel, providing a distillation of the tools and skills needed to be successful in business, whether your business is management of core lab, directing a startup, applying for grants, or all of the above. After a didactic learning phase, teams of trainees with a core facility leader work on defining a solution to an actual business-related problem currently being experienced in the core lab. This session will feature both a trainee and core lab director participant discussing the impact of the course on their personal development and on the functioning of the host facility. It will also present lessons learned on building and sustaining an educational partnership involving core labs.
Session Type: Workshop
The ABRF-NRMN Partnership: Facilitating Professional MentorshipThis presentation will describe the launch of a new, exciting partnership between the ABRF Career Development Committee and the National Research Mentorship Network (NRMN), a nationwide consortium of biomedical professionals and institutions collaborating to provide researchers across the biomedical, behavioral, clinical and social sciences with evidence-based mentorship and professional development programming. The NRMN is an NIH-funded organization that emphasizes the benefits and challenges of diversity, inclusivity and culture within mentoring relationships, and more broadly within the professional research community. Hockberger's presentation will provide an overview of the partnership, the program, and how ABRF members can take advantage of this long-awaited opportunity.
Session Type: Research Group
ABRF-MRG2016 Metabolomics Research Group Data Analysis StudyMetabolomics is an evolving field. One of the major bottlenecks in the field is the varied application of bioinformatics and statistical approaches for pre- and post-processing of global metabolomic profiling data sets collected using high resolution mass spectrometry platforms. Several publications now recognize that data analysis outcome variability is caused by different data treatment approaches. Yet, there is a lack of inter-laboratory reproducibility studies that have looked at the contribution of data analysis techniques toward variability/overlap of results. Thus our study design recapitulates a typical metabolomics experiment where the goal is difference detection of features between two groups. The goal of MRG 2016 study is to identify the contribution of data pre and post processing methodologies on data outcome. Specifically, for this study we have used urine samples (a commonly used matrix for metabolomics-based biomarker studies) from mice exposed to 5 Gray of external beam gamma rays and those exposed to sham irradiation (control group). The data files were made available to study participants for comparative analysis using commonly used bioinformatics and/or biostatistics approaches in their laboratory. The participants were asked to report back top 50 metabolites contributing significantly to the group differences. We have received several responses and the findings from the study are being consolidated for MRG presentation at the ABRF 2017 meeting.
Session Type: Satellite Workshop
Untargeted Global Lipidomics in the Systems Biology Tri-ome EraGlobal profiling of lipids is emerging as a go to -omics technology in recent years as high resolution instrumentation and software improves. Systems biology approaches to understanding the workings of a cell or tumor as it becomes dysregulated from diseases such as cancer are becoming possible with advancements in proteomics, polar metabolomics and non-polar lipidomics. I will focus primarily on our untargeted lipidomics platform that uses a data-dependent acquisition (DDA) strategy with positive/negative polarity switching on a QExactive HF Orbitrap with commercial software for identifying a broad range of lipids and performing alignment and relative quantification (LipidSearch and Elements) (Breitkopf et. al., Metabolomics, 2017). It is all based on MS/MS fragmentation spectra for verifying lipid identifications from a 30 min. high-throughput RP-LC-MS/MS experiment. We will demonstrate the lipidomics platform and its place in systems biology from a serial-omics liquid-liquid extraction from a single cell or tumor sample in breast cancer, multiple myeloma or urine samples whereby the other extraction partitions can be used for other -omics technologies.