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BIOMEDICAL SCIENCES CORE COURSE

IDPT 7811, 7812, 7813, 7814 & 7815

Credits: 10 semester hour

Status: required
This is a set of interdisciplinary courses required for first year graduate students enrolled in basic science Ph.D. programs at UCD-AMC. The objective of the courses is to provide the basic science information and introduction to the skills required for a successful research career in all disciplines of modern biomedical sciences. Topics cover the fundamentals of biochemistry, molecular biology, cell biology, developmental biology, molecular genetics and biomolecular structure. Specialty topics required by individual programs are taken usually during the spring semester of the first year, and in some cases in the second year to round out the curriculum.


OTHER REQUIRED COURSES

CPBS 7605 Ethics in Bioinformatics
Credits:
1 semester hour

Status: required

Discussion of professional conduct, social implications of research and questions raised by biomedical research with an emphasis on topics relevant to computational biologists. Active student participation in required.
 

CPBS 7606 Statistics for the Basic Sciences
Credits:
3 semester hours

Status: required

This course provides an overview of fundamental concepts in statistics such as hypothesis testing and estimation and it provides an overview of statistical methods (for example, regression and analysis of variance) that apply to many areas of science.


CBPS 7711 Methods and Tools in Biomedical Informatics
Credits: 4 semester hours
Prerequisite: permission of instructor
Status: required

What is bioinformatics, and why study it? How is large scale molecular biology data generated, where and how can researchers gain access to it, and what is the quality of the data?

  • Nucleotide sequence data: Genomic sequencing, expressed sequence tags, gene expression, transcription factor binding sites and single nucleotide polymorphisms.
  • Metadata: Summary and reference systems, finding new types of data online, likely growth areas. Private and future data sources Computational representations of molecular biological data, data storage techniques: databases (flat, relational and object oriented), and controlled vocabularies.
  • General data retrieval techniques: indices, Boolean search, fuzzy search and neighboring. Biological data types and their special requirements: sequences, macromolecular structures, chemical compounds, genetic variability, and connections to clinical data. Representations of patterns and relationships: alignments, regular expressions, hierarchies, and graphical models (including Markov chains and Bayes nets).
  • Visualization: methods for presenting large quantities of biological data, particularly sequence viewers, 3D structure viewers, anatomical visualization, and database-driven web sites.
  • Interoperability - the challenges of data exchange and integration: Ontologies, interchange languages and standardization efforts. XML, UMLS, CORBA and OMG/Life Sciences. 
  • Inference problems and techniques for molecular biology with an overview of key inference problems in biology, including: homology identification, genomic sequence annotation, protein structure prediction, protein function prediction, gene expression characterization, network identification, and drug discovery.


CBPS 7712 Research Methods in Biomedical Informatics
Credits: 4 semester hours
Prerequisite: CBPS 7711
Status: required

This course continues to define and discuss inference problems and techniques for molecular biology. Overview of key inference problems in biology: homology identification, genomic sequence annotation, protein structure prediction, protein function prediction, gene expression characterization, network identification, and drug discovery. Machine learning: neural networks, genetic algorithms, simulated annealing. Evaluation of prediction methods: parametric tests, cross-validation and empirical significance testing. Sequence alignment methods: dot plots, dynamic programming, hidden Markov models. Current alignment methods: PSI-BLAST, Needleman–Wunsch, Smith–Waterman. Protein structure predictions: secondary structure, fold recognition, new fold methods. Computer simulation methods: molecular dynamics, Monte Carlo.

Additionally, this course addresses recent developments in bioinformatics and focus on advanced issues in specific areas including (but not limited to) information extraction from biomedical literature, inference of biochemical networks from high–throughput data, and prediction of protein function.
 

CPBS 7650 Research Rotations (2-3 Required)

Credits:  1 semester hour

Prerequisite:  permission of instructor

Status:  required

This requirement is designed to give the student a better understanding of other sciences, promote collaboration between departments, and communicate effectively with biologists and scientists. The student must pick from Associated Faculty and ask permission to join their lab plus decide on a project, complete and submit the pre-rotation laboratory agreement, and deliver a short seminar at the time of completion. It is considered a tool for selecting a dissertation subject.

 

CBPS 8990 Doctoral Thesis
Credits: Minimum 30 semester hours
Prerequisite: successful completion of required bioinformatics courses
Status: required

Doctoral study for the Ph.D. degree by students in Computational Bioscience program only.

 
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