Invited Talk: – 5

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Bioinformatics: Bioinformatics: A New Vision for Academics A New Vision for Academics

2nd International Conference on Frontiers of Information Technology (FIT) 2006

IslamabadPakistan

December 20 - 21, 2006Mudasser F. Wyne, Ph.D.

Computer Science

University of Michigan - Flint

Computer Science Department

Email:

[email protected]

FIT-2006FIT-2006 Mudasser F. WyneMudasser F. Wyne University of Michigan-Flint University of Michigan-Flint

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Bioinformatics??Bioinformatics??

Classically known Computational biology

Definition The storage and analysis of biological data using certain

algorithms and computer software The application of tools of computation and analysis to

the capture and interpretation of biological data Emphasis

Use of computer and statistical methods to understand biological data


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BioinformaticsBioinformatics A multifaceted discipline

Biology Genetics and microbiology

Biochemistry Mathematics Statistics Computer science

AI, Database, Algorithms, Pattern recognition


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BioinformaticsBioinformatics Bioinformatics is a new and rapidly evolving discipline that

has emerged from the fields of experimental molecular biology and biochemistry, and from the artificial intelligence, database, pattern recognition, and algorithms disciplines of computer science.


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Why Bioinformatics?Why Bioinformatics?

Gene information at NCBI doubles every 14 months Computer scientists are needed to

Analyze Index Represent Model Display Process Mine Search


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Why a new Program?Why a new Program?

Non of the traditional programs serve the needs of the new demand

Fundamental challenge Life science curricula have historically shared very little

common ground with computer and IT curricula Traditional science programs in Computer Science and

Biochemistry Information systems are the lifeblood of the new century

A positive feedback cycle where the need for new genomics and biomedical discoveries

Push the development of information systems


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Why a new Program?Why a new Program?

Largely because of the inherently interdisciplinary nature of bioinformatics research, academia has been slow to respond to strong industry and government demands for trained scientists to develop and apply novel bioinformatics techniques to the rapidly growing freely available repositories of genetic data.


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Another ReasonAnother Reason

Decrease in enrollment in computer science programs USA

From 2000 the drop is around 35 to 50% Labor statistics forecast job growth 20% to 50% by

2012 UK

From 2000 the drop is around 20% to 35% Electronics and Electrical engineering enrollment

increased Europe

Enrollments decreasing and jobs are rising


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Interdisciplinary or MultidisciplinaryInterdisciplinary or Multidisciplinary

Multidisciplinary Involvement of several different professional areas Not necessarily in an integrated manner

Interdisciplinary Integration of multidisciplinary knowledge across a

central program theme or focus Creates knowledge that is more holistic than knowledge

built in discipline specific studies


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Why Not Graduate Degree?Why Not Graduate Degree?

Entrance barriers for these programs are high, Significant amount of prerequisite knowledge in the

fields of biochemistry and computer science B.Sc. Computer Science

Remedial courses in chemistry, biochemistry, molecular biology and genetics

B.Sc. Biology Remedial courses in programming, data structure,

database and artificial intelligence


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Why Not Graduate Degree?Why Not Graduate Degree?

I will present an undergraduate-level bioinformatics curriculum in computer science designed for the baccalaureate student.

This program is designed to be tailored easily to the needs and resources of a variety of institutions.


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VariationsVariations

A challenge to discover Mostly offered as subprograms or specializations of

existing programs Several terms

Bioinformatics Medical informatics, Informatics, Health informatics, Computational biology

Most programs have started in just the last 3 years and have not been entered into a program directory.


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Web SearchWeb Search


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School StatisticsSchool StatisticsMichigan National

Schools with undergraduate degrees in Bioinformatics 1 14

Schools with undergraduate tracks in 1

Schools with Masters degrees in Bioinformatics 3 9

Schools with Doctorial degrees in Bioinformatics 1 1

Schools with Graduate tracks in Bioinformatics 1 1

Schools with an undergraduate course in Bioinformatics 2

TOTAL 9 25


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Structural Learning ModelStructural Learning Model

Pre-Structural Level Learner is distracted by an irrelevant aspect belonging

to a previous mode Uni-Structural Level

Learner focuses on a relevant discipline Multi-Structural Level

The learner acquires knowledge is several disciplines But does not integrate them

Relational Level Learner integrates knowledge from several discilpines

around a central theme


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Bioethics(3)

Biostatistics(3)

Bioinformatics(3)

Adv.bioinformatics

(3)

Paper/ Project

(3)

Genomics(3-4)

Genetics (4)

Cell & Molecular Biology

(4)

General Biology II

(4)

General Biology I

(4)

MTH121(4)

MTH122(4)

MTH321(3)

DS & AA(3)

Object Oriented

Prog.(4)

Organic Chemistry II

(4)

Organic Chemistry I

(4)

General Chemistry I

(4)

General Chemistry II

(3)

Prog.(4)

Physics II(4)

Physics I (4)

Database Design

(3)

AI(3)

Data Mining

(3)

Program Flow -1Program Flow -1


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Program Flow -2Program Flow -2Bioethics

(3)

Biostats(3)

Statistics (3)

Bioinformatics(3)

Adv.Bioinfor.

(3)

Paper/ Project

(3)

Genomics(3-4)

Cell & Molecular Biology

(4)

Genetics(4)

General Biology II

(4)

General Biology I

(4)

MTH121(4)

MTH122(4)

MTH321(3)

DS & AA(3)

OO Prog.(4)

BioChemistry(3)

Organic Chemistry II

(4)

Organic Chemistry I

(4)

General Chemistry I

(4)

General Chemistry II

(3)

Prog.(4)

Database Design

(3)

AI(3)

DataMining

(3)

VB(3)

ICS(2)

SW(1)


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Sample Course ContentsSample Course Contents

Bioinformatics Applications of computer-based tools to the representation,

annotation, and analysis of DNA and protein sequences. Computer lab-oriented exercises employing software packages

used to evaluate structural, functional, and evolutionary characteristics of animal and microbial genomes.

Topics Fundamentals of Gene Structure and Function, Molecular Biology

Databases, Information Retrieval, Database Searches, Molecular Sequence Analysis Tools, Gene Identification and Protein Structure-Function Predictions. Computational analysis of DNA data; Introduction to bioinformatics database using Pearl and SQL; configuration of UNIX workstations for bioinformatics analyses.


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Adv. Bioinformatics This course presents an algorithmic focus to problems

in computational biology. Problems and solutions covered in this course include Gene Hunting, Sequence Comparison, Multiple Alignment, Gene Prediction, Trees and Sequences, Databases and Rapid sequence analysis.

Also known as: Bioinformatics, Computational Bioinformatics,

Principles of Bioinformatics II , Advanced Bioinformatics Computing,


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Bioethics Discussions of major ethical questions having arisen

from research in genetics, medicine, and industries supported by this knowledge.

Topics General scientific ethics, biological research ethics,

governmental and research policy issues. Course work I primarily reading and writing


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Credit HoursCredit Hours

Credit Hours Maths: 11 Biology: 19 +3 (Biostatistics) + 3

(Bioinformatics) Chemistry: 18 CS: 23 + 3 (Project) Philosophy 3 (Bioethics) Total hours: 83


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AccreditationAccreditation

This model program can be modified to meet CSAB requirements ABET Computer science topics at least 40 semester hours Mathematics and science at least 30 semester hours Humanities, social sciences, arts and other disciplines

that serve to broaden the background of the student at least 30 semester hours.


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QUERIES QUERIES


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2nd International Workshop on 2nd International Workshop on Web-Based Learning: Innovation and ChallengesWeb-Based Learning: Innovation and Challenges

(WeLearn-2007) (WeLearn-2007)Amman, Jordan, Amman, Jordan, 17–20 April 200717–20 April 2007

Aims and Scope

The focus of this workshop is on web based issues in both teaching and learning. We would also like to stimulate interest in this area, expose natural collaboration among the participants, inform the larger research community of the interest and importance of this topic and create a permanent forum for evaluating innovations and relevant research activities.

Paper submission deadline: January 20, 2007.

Send you submissions to [email protected].

Invited Talk: – 5

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