The four core courses offered by the program and their descriptions are as follows:

IB 301 – System Biology for Engineers and Computer Scientists

Instructors: Drs. Aydin Tozeren and Peter I. Lelkes (Drexel), Dr.Warren Ewens (U Penn).

DESCRIPTION: System biology studies biological systems by systematically perturbing them (biologically, genetically, or chemically); monitoring the gene, protein, and informational pathway responses; integrating these data; and ultimately, formulating mathematical models that describe the structure of the system and its response to individual perturbations (5). This course brings a system engineering approach in providing the foundations of molecular cell biology, namely, the robust complex network of genes and proteins, cells as the basic units of life, communication of cells with other cells and the environment, and finally, the gene circuits governing the development of animals. The tools of molecular bioinformatics are used throughout the course to advance the fundamental topics in molecular biology.

TEXT: Tozeren and Byers (2003), New Biology for Engineers & Computer Scientists, Prentice Hall, NJ and selected research articles.

COURSE OBJECTIVES:
1)      To introduce the fundamentals of molecular system biology to engineering and computer science students.
2)      To introduce the students to recent advances in functional genomics and proteins and enabling technologies such as microarrays, microfluidic chips, 2D gels, and mass spectroscopy.
3)      To introduce the reader to the enabling computing technology of bioinformatics in solving problems related to system biology.

CONTENTS
Chemistry of Life: atoms, molecules and covalent bonds; ionic compounds and electrostatic bonds; water and hydrogen bonds; lipids and Van Der Waals attraction; acids and bases; chemical reactions and enzymes.

Macromolecules of Life: Carbohydrates; lipids; nucleic acids DNA & RNA; amino acids and proteins; genetic code; protein structure and function; flow of information from DNA to protein.

Cells: Prokaryotes and Eukaryotes; nucleus; organelles for protein synthesis and transport; metabolic processes and mitochandria; actin motor proteins: cytoskeleton myosin and kinesin; cell membrane; mitochondria: power plants of eukaryotic cells; cell active membrane transport. 

Gene Circuits:  From Gene Recipe to the Manufacturing of Protein; gene anatomy and regulatory sequences; gene circuits and genetic regulatory network of the cell; protein-protein interactions and two-hybrid arrays; topology of protein networks; pathways for the propagation of phosphorylation and other signals.

Genomics: History and Evolution of the Genome; sequence similarity and homologous genes; shotgun approach for decoding genomes (cutting and sizing DNA, making multiple copies; sequencing; assembling overlapping pieces); gene annotation; perturbed and modified genomes; system biology experiments in the yeast.

Cell Communication: Modes of Cell Communication; extracellular matrix and integrins; cell-cell adhesion and cadherins; signal transduction pathways; crosstalk between pathways; cell division cycle; cell cycle check points.

Development of Multicellular Organisms: From unfertilized Egg to Zygote; cleavage: first stage of development; gastrulation; pattern-generating genes; stem cells and tissue engineering.

IB 302 – Database Systems and Data Mining in Molecular Biology

Instructors: Dr. Susan Davidson (U Penn), Dr. Il-Yeol Song (Drexel)

DESCRIPTION: This course presents a foundation of modern database systems and data mining techniques for system biologists. The course covers data modeling using the Entity-Relationship model and object-oriented models, fundamentals of relational database systems, standard query language SQL, and a survey of data mining techniques used in bioinformatics research.

TEXT: Locally produced lecture notes and selected research articles.

COURSE OBJECTIVES:
1)      To introduce the fundamentals of data modeling techniques based on the Entity-Relationship model.
2)      To introduce the advanced modeling technique using object-oriented models
3)      To introduce the students the principles of relational database systems and the query language SQL
4)      To introduce the unique requirements of representing and analyzing bioinformatics data using modern database technology
5)      To introduce a survey of data mining techniques used in bioinformatics research

CONTENTS:
1)      Introduction to database systems (5%)
2)      Data modeling using the Entity-Relationship model (15%)
3)      Advanced data modeling using object-oriented approaches (10%)
4)      Principles of relational database systems (20%)
5)      SQL (10%)
6)      Data modeling and analysis in Bioinformatics (10%)
7)      A Survey of data mining techniques for systems biologists (30%)

IB 303 – Transcriptase and Proteomic Informatics

Instructors: Dr. Richard Somiari (Windber), Drs. Joseph Foley, Brad Jameson & Jian-Min Yuan (Drexel).

DESCRIPTION: This course is designed to provide students with hands-on experience in the discovery of disease-associated genes and proteins, as well as in the overall analysis of microarray and proteomics data. Proteomics refers to the protein content of cells and tissues and is a field of science encompassing a wide variety of topics including 3D protein structure, homology modeling, and protein expression mapping. Recent research has uncovered significant differences in the protein content of healthy and diseased tissue. Experimental and bioinformatics tools associated with gene expression profiling and protein expression maps are increasingly being used in clinical setting. The course will focus on sources of possible error in the microarray and proteomics data, signal processing of data, and clustering profiles via pattern recognition techniques such as supervised learning.

PREREQUISITES: None

TEXT: Locally produced lecture notes and selected research articles.

COURSE OBJECTIVES:
1)      To introduce the students to the fundamentals of transcriptase and proteomic informatics.
2)      To introduce the students to recent advances in enabling technologies associated with proteomics such as protein micro-arrays, high throughput 2D gels, mass spectroscopy, and X-ray and NMR techniques for protein structure imaging.
3)      To introduce the students to the enabling computing technology of bioinformatics in solving problems related to system biology.

CONTENTS
Overview: Information flow from genes to proteins; amino acids found in proteins; biophysical and biochemical properties; synthesis of proteins; primary, secondary, and tertiary structure of proteins; post translational modifications, gene and protein networks.

Gene Expression Studies by Microarrays, ESts and SAGE; signal processing and clustering analysis of microarray profiles; pathway analysis; differential expression; multi-gene analysis.

Protein Expression Analysis & Mass Spectroscopy; primary, secondary and tertiary structures of proteins; post transcriptional protein modification.

Large Scale Proteomic Tools: 2D gels; mass spectroscopy; computational pattern recognition for proteomics.

3D Structure of Proteins: X-ray crystallography; NMR imaging; fluorescent based molecular imaging; homology modeling; protein networks and pathways: KEGG database presentation of signal transduction pathways.

IB 304 – Gene and Genome Informatics

Instructors: Dr. Sampath Kannan (U Penn), Drs. Mark Lechner and Aydin Tozeren (Drexel)

DESCRIPTION: This course is designed to provide students with hands-on experience in functional genomics. Topics discussed include structure and anatomy of DNA, shotgun and other methods used in decoding DNA, genes, operons, gene circuits, gene mapping, gene expression profiling, homology, clusters of ortholog genes, gene annotation, gene mapping, and experimental perturbation of genomes for medical purposes. Examples presented in the course illustrate the role of functional genomics in drug design, gene discovery, and in designing individual therapies for a variety of diseases and disorders. The course will introduce and use biological data sources available on the World Wide Web media.

Reference Text: Mount, D.W., Bioinformatics: sequence and genome analysis. 2001, Cold Spring Harbor, NY: ColdSpringHarbor Laboratory Press. xii, 564. ISBN: 0879696087.

COURSE OBJECTIVES:
1)      To introduce the students to the fundamentals of functional genomics.
2)      To introduce the students to recent advances in enabling technologies associated with genomics such as recombinant DNA, vector insertion, and sequencing.
3)      To introduce the students to the concepts of homology, ortholog and paralog genes, gene families, gene annotation, and gene mapping.
4)      To introduce the students to the enabling computing technology of bioinformatics in solving problems related to system biology.
5)      To introduce the students to recent advances in algorithms and tools used in management, clustering, and analyzing in computational biology,
6)      Use of biological data sources available on the World Wide Web media.

CONTENTS

Decoding DNA: cutting and sizing DNA, making multiple copies, sequencing, integrating sequenced data.

Genes: gene anatomy, gene circuits, sequence similarity and homologous genes; gene and protein families.

Genomic and Genetic Mapping: study of mapping, map construction; physical mapping; genetic markers; linkage maps.

Gene Hunting and Gene Annotation: functional cloning; positional cloning; positional candidate identification; mapping of functional clones; identification of candidate genes

Phylogeny: similarity-based methods, parsimony and maximum likelihood studies.

Functional Genomics: yeast genome studies; plants and animals with modified genomes; recent research on functional genomics.