A unique curriculum has been designed to provide training to span the disciplines of translational environmental health sciences. This curriculum takes the place of the Graduate Group electives and is designed not to delay the time to attain the PhD degree. Upon completion of the didactic curriculum, trainees will have completed the requirements for the Certificate in Environmental Health Sciences. Upon completion of their thesis, trainees will receive the Certificate in Environmental Health Sciences and a PhD from their graduate group.
Curriculum for Certificate Program in Environmental Health Sciences
Cell Biology & Biochemistry – BIOM 600 (1.0 c.u.)
Experimental Genome Science – GCB 534 (1.0 c.u.)
Required Graduate Group Elective or Rotation (2.0 c.u.)
Molecular Toxicology – PHRM 590 (1.0 c.u.)
Data Analysis for Life Science – BIOM 610 (1.0 c.u.)
Required Graduate Group Elective or Rotation (2.0 c.u.)
Community Environmental Health Rotation (1.0 c.u.)
Laboratory Rotation (1.0 c.u.)
Data Science for Biomedical Informatics – BMIN 503 (1.0 c.u.)
Environmental Epidemiology – EPID 711 (1.0 c.u.)
Graduate Group Electives (2.0 c.u.)
Thesis Proposal – Independent Study (2.0 c.u.)
Candidacy Examination (2.0 c.u.)
Enter Thesis Research Laboratory
Students are required to do three rotations. One rotation can be taken in the summer before matriculation. One rotation must involve a mentored community-based experience or epidemiology/population based study. Rotations must be done in the lab of a CEET investigator.
Cell Biology and Biochemistry: BIOM 600 (Mandatory)
BIOM 600 is a beginning-to-intermediate-level graduate school course designed to introduce students to the molecular components and physiological mechanisms that underlie the structure and function of eukaryotic cells. The course emphasizes core cell biology concepts by describing both landmark experiments and methods as well as current scientific research questions and technical approaches.
Experimental Genome Science: GCB 534 (Mandatory)
This course will survey methods and questions in experimental genomics, including next generation sequencing methods, genomic sequencing in humans and model organisms, functional genomics, proteomics, and applications of genomics methods. Students will be expected to review and discuss current literature and to propose new experiments based on material learned in the course.
Molecular Toxicology: PHRM 590 (Mandatory)
Exposures to foreign compounds (drugs, carcinogens, pollutants) can disrupt normal cellular processes leading to toxicity. This course will focus on the molecular mechanisms by which environmental exposures lead to end-organ injury and to diseases of environmental etiology (neurodegenerative and lung diseases, reproduction disruption and cardiovascular injury). Students will learn the difficulties in modeling response to low-dose chronic exposures, how these exposures are influenced by metabolism and disposition, and how biological reactive intermediates alter the function of biomolecules. Mechanisms responsible for cellular damage, aberrant repair, and end-organ injury will be discussed. Students will learn about modern predictive molecular toxicology to classify toxicants, predict individual susceptibility and response to environmental triggers, and how to develop and validate biomarkers for diseases of environmental etiology. Students are expected to write a term paper on risk assessment on an environmental exposure using available TOXNET information.
Data Analysis for Life Science: BIOM 610 (Mandatory)
Technological advances have transformed fields that rely on data by providing a wealth of information ready to be analyzed. From working with single genes to comparing entire genomes, biomedical research groups around the world are producing more data than they can handle and the ability to interpret this information is a key skill for any practitioner. The skills necessary to work with these massive datasets are in high demand, and this course will help you learn those skills. Using the open-source R programming language, you’ll gain a nuanced understanding of the tools required to work with complex life sciences and genomics data. You’ll learn the mathematical concepts — and the data analytics techniques — that you need to drive data- driven research. From a strong foundation in statistics to specialized R programming skills, this course will lead you through the data analytics landscape step-by-step.
Data Science for Biomedical Informatics: BMIN 503 (Mandatory)
This course will use R and other freely available software to learn fundamental data science applied to a range of biomedical informatics topics, including those making use of health and genomic data. After completing this course, students will be able to retrieve and clean data, perform exploratory analyses, build models to answer scientific questions, and present visually appealing results to accompany data analyses; be familiar with various biomedical data types and resources related to them; and know how to create reproducible and easily shareable results with R and github.
Environmental Epidemiology: EPID 711 (Mandatory)
Environmental Epidemiology is an advanced epidemiology course that addresses epidemiological research methods used to study environmental exposures from air pollution to heavy metals, and from industrial pollutants to consumer product chemicals. The course will provide an overview of major study designs in environmental epidemiology, including cohort studies, panel studies, natural experiments, randomized controlled trials, time-series, and case-crossover studies.
The following electives are highly recommended:
Introduction to Superfund Sites and Health Effects of Hazardous Waste: PHRM 657 / ENVS 657 Superfund hazardous waste sites are prevalent in our nation and the exposures to toxicants from these sites raises, immediate public health concerns. The aims of this course are to educate students about these sites and provide a scientific basis for hazard identification, hazard characterization, risk communication and risk management. The course will describe the effect of these hazardous chemicals on the ecosystem and vice-versa and remediation and mitigation approaches. These environmental science issues will lead into the environmental health aspects of exposures including: bio-monitoring (external and internal dose, biomarkers and the exposome), toxicological properties of contaminants and mode-of-action. The course will be complemented with visits to two Superfund sites in the region: Ambler (Asbestos) and Palmerton (Heavy Metals).
Methods for Statistical Genetics in Complex Human Disease: BSTA 787
This is an introductory course for graduate students in Biostatistics, Statistics, Epidemiology, Bioinformatics and other BGS disciplines which will cover statistical methods for the analysis of family and population based genetic data. Topics covered will include allele frequency estimation, classical segregation and linkage analysis, multipoint linkage tests, general pedigree analysis, family-based association analysis and population based haplotype analysis. Students will be exposed to the latest statistical methodology and computer tools on gene mapping in complex human disease. They will also read and evaluate current statistical human genetics literature.
Mechanisms of Disease: BIOM 502
During BIOM 502, several human diseases will be studied, focusing on the mechanism of the disease, the clinical presentation and how our understanding of the disease mechanism affects current treatment regimens and well as offers research opportunities for new approaches to treatment. The specific diseases studied change yearly. Some of the diseases studied in prior years include diabetes, breast cancer, colon cancer, HIV / AIDS, and atherosclerosis. Student obtain background information via the medical school “Virtual Curriculum” and read and discuss papers weekly. Grading is based on a presentation at the end of the course demonstrating the connection between mechanism, clinical presentation and treatment in a disease of the student’s choice.
Neurotransmitter Signaling & Neuropsychopharmacology: PHRM 510
Course provides a general overview of the signaling properties of the nervous system. Also provides in-depth information on neurotransmitter and associated signaling systems. Emphasis is placed on the wealth of new molecular information that is being gathered to examine how cells of the nervous system function and communicate.
Introduction to Bioinformatics: MTR 535. Course directors: Benjamin F. Voight, PhD and Casey S. Greene, PhD. This course provides broad overview of bioinformatics and computational biology as applied to biomedical research. A primary objective of the course is to enable students to integrate modern bioinformatics tools into their research activities. Course material is aimed to address biological questions using computational approaches and the analysis of data. Areas include DNA sequence alignment, genetic variation and analysis, motif discovery, study design for high-throughput sequencing, RNA and gene expression, single gene and whole-genome analysis, machine learning, and topics in systems biology. The relevant principles underlying methods used for analysis in these areas will be introduced and discussed at a level appropriate for biologists without a background in computer science. However, a basic primer in programming and operating in a UNIX environment will be presented, and students will also be introduced to Python, R, and tools for reproducible research. This course emphasizes direct, hands-on experience with applications to current biological research problems.