Core Principles
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Data/Tech Fluency: Understand the basic operation and function of the platforms (e.g., next-generation sequencing, mass spectrometry, NMR) and recognize and work with various data formats
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Rigor: All steps in the experimental design process, including power calculations, controls, and methods to assess data quality, must be clearly understood and articulated
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Metabolic Pathways Knowledge: Emphasize and understand the basics of metabolism and its relation to host-microbiome interactions
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Transparency: All data acquisition, processing, and analysis steps must be clearly described using documented methods and freely available tools
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Reproducibility: All data acquisition, processing, and analysis steps must be repeatable by second parties and generate equivalent results
Key Proficiencies
Knowledge
The trainee will understand fundamental concepts in metabolism, microbiome sciences, genomics, analytical chemistry, and the platforms used to generate these data. Trainees must be able to develop and use computational and statistical tools to address scientific questions in these areas
Problem Solving
The trainee will demonstrate advanced research skills, including developing hypotheses, research design, data analysis, and interpretation
Communication
The trainee will be skilled in communicating research findings in written and spoken presentations to disciplinary experts and other stakeholders, such as the general public, news media, policymakers, or venture capitalists interested in funding intellectual property development projects
Key Skill Development
Scientists have an obligation to clearly explain their research to diverse audiences that include the public, business persons, and policymakers, as well as scientific peers and colleagues. The trainee will gain communication experience through coursework, summer research projects, teaching, and experiential learning exercises to improve their ability to communicate effectively and persuasively to multiple audiences.
Quantitative Expertise
Trainees must exhibit a solid understanding of the quantitative fields emphasized in this program, especially around analyzing metabolomics and microbiome data. We rely on required coursework to ensure that all students have basic quantitative skills in computing, statistics, and metabolomics/genomics (see course list) and on experiential learning (e.g., workshops, interaction with the facility directors) activities to develop and apply these skills.
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Computational skills: Trainees should be able to understand scientific software and use existing tools for data mining, processing, and alignment. This includes a fundamental understanding of tools available for studying the metabolome and microbiome. Data analysis workshops like DAWG and hands-on laboratory training will teach computational skills and reinforce best practices.
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Statistical skills: Trainees must understand the basic theory underpinning standard and Bayesian statistics as well as machine learning approaches and be able to apply these approaches using scripting languages packages (such as R or Python) to perform exploratory data analysis, hypothesis testing, effect size estimation, classification, clustering, and predictive modeling. Statistical skills will be introduced in coursework (Block 4, see below) through the instrument and data analysis groups and reinforced during the R&R discussions.
Biological Expertise
Trainees should be able to ask questions related to metabolism (host and microbiome) that are enabled by data of the magnitude and complexity now available from modern metabolomics and genomics tools available through our technology cores. We rely on required coursework to ensure all students understand research design, metabolism, microbiology, and analytical chemistry.
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Research design: Trainees must demonstrate advanced research skills concerning questions in the life sciences, including designing a proposal to test a hypothesis and critically evaluating data generated in light of this hypothesis. Coursework, bi-weekly meetings, instrument and data analysis groups, and laboratory training will be integrated to guide and assist with developing trainee research design expertise.
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Metabolism: Trainees must demonstrate their knowledge of metabolism and apply it to their interpretation, for example, of metabolomics and microbiome data. IAMP trainees will gain knowledge through coursework (Block 5, see below), the Metabolomics Users Group, seminars, trainee meetings, and hands-on training.
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Technology: Trainees must understand the molecular basis behind methods used to study the metabolome and microbiome, such as mass spectrometry, NMR, and sequencing-based analysis. Coursework (Block 6), instrument user groups, and hands-on training will disseminate information on state-of-the-art technology used for metabolism research.
Communication Expertise
Scientists have an obligation to clearly explain their research to diverse audiences that include the public, business persons, and policymakers, as well as scientific peers and colleagues. The trainee will gain communication experience through coursework, summer research projects, teaching, and experiential learning exercises to improve their ability to communicate effectively and persuasively to multiple audiences.
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Basic research communication: All trainees must demonstrate their capacity for critical thinking, listening, generating ideas, and communicating their research in written and oral presentations. Presentations will occur during bi-weekly trainee meetings, coursework presentations, research lab meetings, and required graduate program exams and committee meetings, all of which will allow IAMP training faculty to provide feedback and guidance to trainees in best practices for communicating their research.