Sign In
Skip Navigation Links.
Expand AboutAbout
Programs & Degrees
Our People
Expand Quick LinksQuick Links
Expand MediaMedia

Bachelor of Science in Biomedical Informatics

College of Computing and Informatics
Computer Science
Study System
Total Credit Hours
124 Cr.Hrs
4 Years
Fall & Spring
Sharjah Main Campus
Study Mode
Full Time

Bachelor of Science in Biomedical Informatics

Become an informatics leader in bioinformatics, pharmaceutical, clinical, or health care industries with a qualification from one of the UAE leading universities.


The field of Biomedical Informatics has now become a key player in both medical research and education and has been implemented in diverse medical subjects including epidemiology, genetics, surgery, cell and molecular biology and pathology. The bachelor in Biomedical Informatics (BSc-BI) is designed to provide a multidisciplinary knowledge and skills to the students, enabling them to work in the various tracks related to biomedical informatics with many career options lying ahead. BSc-BI is designed to prepare students for careers in the emerging and vital field of biomedical informatics.  The program enables the students to build solid technical foundation in Biomedical Informatics and to become an informatics leader in the bioinformatics, pharmaceutical, clinical, or health care industries.


The BSc in Biomedical Informatics is designed to provide a multidisciplinary knowledge and skills to the students, enabling them to work in the various tracks related to biomedical informatics with many career options lying ahead. The United Arab Emirates (UAE) has addressed in its 2021 vision the importance of providing world-class healthcare, which can be boosted by this program providing innovative and skilled graduates. 

The implementation of this program is consistent with the vision and mission of the University of Sharjah (UoS), which is to educate through the academic process, to further human discovery through research, and to enhance wellbeing through involvement with the community.

The BSc in Biomedical Informatics is an integral component of the different existing programs from different colleges at the University of Sharjah such as College of Computing and Informatics, College of Sciences, and College of Medicine.  The proposed program will offer an opportunity for students to gain knowledge and skills in the fields of biomedical and health informatics providing them with the chance of better job opportunities with higher salaries. More importantly, the program will benefit the UAE economy by producing skilled scientists that are able to contribute in the biomedical informatics field.

Entry Requirement

  1. Completion of secondary education or an equivalent level with the required average no earlier than three years prior to joining the University.
  2. Students must meet the English language proficiency requirement of a score of 1400 in the EmSAT English exam, or 500 in TOEFL (ITP) (or its equivalence), or 6 in IELTS.

Program Goals

The goals of the program are to:
  1. Engage in a successful career in diverse areas of biomedical or health informatics or be able to pursue advanced degrees in a related field.
  2. Analyze a complex biomedical informatics problem and to apply principles of computing & informatics and other relevant disciplines to identify solutions.
  3. Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of biomedical informatics.
  4. Communicate effectively in a variety of professional contexts.
  5. Recognize professional responsibilities and make informed judgments in biomedical informatics practice based on legal and ethical principles.
  6. Function effectively as a member or leader of a team engaged in activities appropriate to the program's discipline.

Program Learning Outcomes

Upon the successful completion of the program, students will be able to:
  1. Apply knowledge of mathematics, computer science, computer engineering, and computational biology appropriate to the discipline.
  2. Analyze a problem, identify and define the computing requirements appropriate to its solution.
  3. Design and evaluate a software system, process, or program to meet desired needs.
  4. Function effectively on teams and communicate effectively with a range of audiences.
  5. Identify professional, ethical, legal, security and social issues and responsibilities related to biomedical informatics.
  6. Analyse the local and global impact of biomedical informatics on individuals, organizations, and society.
  7. Apply design and development principles in the construction of software and informatics-based solutions of varying complexity.

Curriculum and Coursework

This program is designed to deliver courses on essential computer science topics and courses on a variety of career paths related to computational biology, bioinformatics, and data analytics using various computational techniques to extract meaningful data from big data resources. In the final year, students will develop senior capstone projects that benefit from algorithmic principles, and computer science theory in the modelling and in line with the latest industry needs for building Biomedical Informatics Systems. Senior students are required to perform practical training in industrial or governmental organization to improve their understanding and provide them with real-world experience of Biomedical Informatics Systems in real work environment and the measures to improve them. 


Graduates of the program can work in governmental agencies, private, and international organizations such as hospitals, medical centers, consultant for healthcare insurance companies, and universities, among others. Working positions range from research work at research institutes, academic work at universities, software engineers at software companies, hospitals, pharmaceutical companies and healthcare laboratories. In particular, graduate of the program can work as a clinical data manager, clinical systems analysts, consultants, researchers, developers, and project supervisors/managers, or quality support analysts.


Program Overview

The program is designed to satisfy the curricular requirements of the ACM/IEEE-CS curricular task force and other relevant professional accreditation bodies, such as CSAC/CAAB. A student undertaking this program should complete a total of 123 credits distributed as follows:

BSc in Biomedical Informatics (124 credits) ​ ​ ​
Mandatory Core Credits1891109
Support Credits---
Electives Credits6915


Program Duration: The normal duration of the program is eight semesters (four years).
Mode of Study: Full-time​

I. University Requirements / Electives

The list of the 24 credits of university required (18) and elective (6) courses with their descriptions is presented in the university catalogue.

II. Program Requirements

The program requirements of 100 credit hours are divided into two major sets.

  1. Biomedical Informatics mandatory core courses (91 credits)
  2. Biomedical Informatics program elective courses (9 credits)


Mandatory Core Courses

This set consists of 91 credit hours listed below.

Course #Course TitleCr. Hr.Prerequisite
900101Human Biology 13None
900307Intro. to System Biology Modelling3None
900324Biomedical Ethics1None
900409Computational Genomics31501332, 1501364
900412Statistical Genomics31440281
1420101General Chemistry (1)3None
1420102General Chemistry (1) Lab11420101
1430113Physics for Medical Sciences3None
1440131Calculus I3None
1440211Linear Algebra I31440131
1440281Intro Probability & Statistics31440131
1450101General Biology 13None
1450102General Biology 231450101
1450107General Biology Lab11450101
1450303Bioinformatics Lab114503202
1450341Molecular Genetics31450102
1450453Protein Biotechnology & Eng.31450102
1501116Programming I4None
1501211Programming II31501116
1501215Data Structures31501211
1501250Networking Fundamental s31501215
1501263Intro. to Database Management System31501215
1501279Discrete Structures31440131
1501318Programming for Bioinformatics31501116
1501330Introduction to Artificial Intelligence.31501215
1501332Machine Learning for Bioinformatics31440131, 1440281, 1501215
1501364Big Data Analytics3 1501263, 1501318, 1440281
1501371Design & Analysis of Algorithms31501279, 1501215
1501391Junior Project in Bioinformatics21501318, 1450302, 1501332
1501392Practical Training - BI3Completion of 90 credits
1501435Medical Image Processing31501332, 1501371
1501497Senior Project in Bioinformatics31501391


Elective Courses

Every student in the Biomedical Informatics must take 9 credit hours of elective courses chosen from the list given in the table below. The choice of these elective courses is designed to meet the breadth and depth requirements in Biomedical Informatics.​

Course #Course TitleCr. Hr.Prerequisite
1427241Molecular Modelling31420101, 1420112, 1450453
1450250Molecular and Cell Biology31450102 
1501341Web Programming3 1501116
1501352Operating Systems31501215
1501365Advanced Database System3 1501263
1501452Introduction to IoT Systems3 1501250
1501454Cloud Computing3 1501215
1501455Database Security3 1501263, 1501459
1501457Data Hiding3 1501215, 1501352
1501459Information Security3 1501215
1501490Topics in Computer Science I3 1501215
1501491Topics in Computer Science II3 1501215
1502201Digital Logic Design3 1501100
1502442Network Programming3 1502346, 1501116


Study Plan

Year I, Semester 1 (16 Credits) ​ ​ ​
Course #TitleCr. Hr.Prerequisites
201102Arabic Language3 
202112English for Academic Purposes3 
1501100Intro. to IT(English)3 
1440131Calculus I3 
1450101General Biology 13 
1450107General Biology Lab11450101


Year I, Semester 2 (14 Credits) ​ ​ ​
Course #TitleCr. Hr.Prerequisites
 University Elective 13 
1501116Programming I4 
1440211Linear Algebra I3 
1420101General Chemistry (1)3None
1420102General Chemistry (1) Lab11420101 or 0215101


Year 2, Semester 1 (18 Credits) ​ ​ ​
Course #TitleCr. Hr.Prerequisites
104100Islamic Culture3 
 University Elective 23 
1501211Programming II31501116
1450102General Biology 231450101
1501279Discrete Structures31440131
302200Fund. of Innovation & Entrepreneurship3 


Year 2, Semester 2 (18 Credits) ​ ​ ​
Course #TitleCr. Hr.Prerequisites
204102UAE Society3 
1501318Programming for Bioinformatics31501211
1501215Data Structures31501211
1440281Intro Prob. & Stat.31440131
900101Human Biology 13None
1430113Physics for Medical Science3 



Year 3, Semester 1 (14 Credits) ​ ​ ​
Course #TitleCr. Hr.Prerequisites
1501263Intro. to DB Manag. Sys.31501215
900324Biomedical Ethics1 
1501330Introduction to Artificial Intelligence 31501215, 1501279
1501332ML for Bioinformatics31440131, 1440281, 1501215
1450302Bioinformatics31450102, 1501116
1450303Bioinformatics lab1 



Year 3, Semester 2 (17 Credits) ​ ​ ​
Course #TitleCr. Hr.Prerequisites
1501250Networking Fundamentals 31501215
1501364Big Data Analytics3 1501263, 1501318, 1440281
1450341Molecular Genetics31450102
1501391Junior Project in Bioinformatics21501318, 145302, 1501332
1501371Design & Analysis of Algorithms31501279, 1501215
1501392Practical Training - BI3Completed 90 credit hours


Year 4, Semester 1 (15 Credits) ​ ​ ​
Course #TitleCr. Hr.Prerequisites
1501497Senior Project in Bioinformatics31501391
1501435Medical Image Processing31501332, 1501371
900420Introduction to Systems Biology Modelling3 
 Program elective 13 
 Program elective 23 


Year 4, Semester 2 (12 Credits) ​ ​ ​
CourseTitleCr. Hr.Prerequisites
900409Computational Genomics31501332, 1501364
1450453Protein Biochemistry & Eng.31450102
900412Statistical Genomics 3 
 Program Elective 33 


Courses Descriptions

Mandatory Core Courses

Description of the core courses are given below:


1501100                Introduction to IT (English)                                                        (2-2:3)
Prerequisite: None

The Course explains what a computer is and what it can (and can't) do; it clearly explains the basics of information technology, from multimedia PCs to the internet and beyond. It illustrates how digital devices and networks affect our lives, our world, and our future. In addition, the course is intended to equip students with the necessary skills to use computer and essential software applications effectively in order to better prepare them for their professional careers.


1501116                Programming I                                                                                 (3-2:4)
Perquisite: None

This course introduces basic program­ming techniques with a high-level pro­gramming language. Topics include gen­eral introduction to computers and num­bering systems, program development process, variables, data types, expres­sions, selection and repetition structures, functions/procedures, text files, arrays, and pointers.


1501211               Programming II                                                                                              (2-2:3)
Prerequisite: 1501116 Programming I

This course introduces fundamental con­ceptual tools and their implementation of object-oriented design and program­ming such as: object, type, class, imple­mentation hiding, inheritance, paramet­ric typing, function overloading, poly­morphism, source code reusability, and object code reusability. Object-Oriented Analysis/Design for problem solving. Implementation of the Object-Oriented programming paradigm is illustrated by program development in an OO language (C++).


1501215                Data Structures                                                                                               (3-0:3)
Prerequisite: 1501211 Programming II

Basics of algorithm design. Linear Structures: Multidimensional arrays and their storage organization, Lists, Stacks and Queues. Introduction to recursion. Nonlinear structures: trees (binary trees, tree traversal algorithms) and Graphs (graph representation, graph algorithms). Elementary sorting and searching methods: bubble sort, quick sort, sequential search, and binary search algorithms.


1501250                Networking Fundamentals                                                         (3-0:3)
Prerequisite: 1501214 Programming with Data Structures

Foundation knowledge for computer networks and communications. Topics include basic network design, layered communications models, IP addressing and subnets, and industry standards for networking media and protocols, with an emphasis on TCP/IP protocol suite and Ethernet environments.


1501263               Introduction to Database Management Systems                            (3-0:3)
Prerequisite: 1501215 Data Structures

This course explores how databases are designed, implemented, and used. The course emphasizes the basic concepts/terminology of the relational model and applications. The students will learn database design concepts, data models (the Entity-Relationship and the Relational Model), SQL functional dependencies and normal forms. The students will gain experience working with a commercial database management system.


1501279                Discrete Structures                                                                        (3-0:3)
Prerequisite: 1440131 Calculus I

This course emphasizes the representa­tions of numbers, arithmetic modulo, radix representation of integers, change of radix. Negative and rational numbers. Sets, one-to-one correspondence, proper­ties of union, intersection, and comple­ment, countable and uncountable sets. Functions: Injective, subjective, and bijec­tive functions. Mathematical Induction, proof by contradiction. Combinatory: Multiplication rule, Pigeonhole principle, Recurrence relations. Fundamentals of logic, truth tables, conjunction, disjunc­tion, and negation, Boolean functions, and disjunctive normal form. Logic circuits. Graphs theory: Introduction, Paths and connectedness, Eulerian and Hamiltonian Graphs, Graph Isomorphisms, coloring of graphs. Trees: Spanning trees, Binary Search Trees, Huffman Code.



1501318                Programming for Bioinformatics                                                                             (3-0:3)
Prerequisite: 1501116 Programming I

This course introduces the fundamentals of programming to solve biological data analysis problems. The course cover topics such as programming basics: attributes, types of objects, sequence generating and vector subset, types of functions, data structure. Object-oriented programming in R for problem solving. Data technologies, Input and output in R, debugging and profiling.



1501330               Introduction to Artificial Intelligence                                   (3-0:3)
Prerequisite: 1501215 Data Structures

This course will provide an introduction to the fundamental concepts and techniques in the field of artificial intelligence. Topics covered in the course include: problem solving and search, logic and knowledge representation, planning, reasoning and decision-making in the presence of uncertainty, and machine learning. Areas of application such as knowledge representation, natural language processing, expert systems, and robotics will be explored. AI programming languages (LISP/Prolog) will also be introduced.



1501332                ML for Bioinformatics                                                                  (3-0:3)
Prerequisite: 1440131 - Calculus I, 1440281 - Intro Probability & Statistics, 1501215 - Data Structures               

Machine learning is one of the major technologies in bioinformatics, used in various domains and applications. The objective of this course is to introduce the students to the fundamental machine learning algorithms and techniques used for acquiring, processing, and extracting useful insights from biological data. The course will present practical solutions to modern bioinformatics problems using Python language. The approach will be hands-on; and will address important topics, such as next- generation sequencing, genomics, population genetics, phylogenetics, and proteomics. The students will learn about probabilistic models, inference and learning in these models, model assessment, and interpreting inferences to address the biological question of interest.


1501364                Big Data Analytics                                                                          (3-0:3)
Prerequisite: 1501263 - Introduction to Database, 1501318 - Programming for Bioinformatics , 1440281 - Introduction to Probability and Statistics

This course introduces fundamental concepts, key technologies, techniques and tools used in the analysis of big data. Topics include: Data analytics lifecycle, basic data analytics methods using R, advanced analytical theory and methods such as: clustering, association rules, regression, classification, time series analysis, text analysis, data analytics technology and tools: MapReduce and Hadoop, in-database analytics, communicating and operationalizing an analytics project, data visualization.




1501371                Design and Analysis of Algorithms                                                          (3-0:3)
Prerequisite: 1501215 Data Structures, 1501279 Discrete Structures

This course emphasizes the fundamental concepts of analyzing and designing algorithms, including divide and conquer, greedy methods, backtracking, randomization, and dynamic programming. A number of algorithms for solving problems which arise often in applications of Computer Sciences are covered, including sorting, searching, graph algorithms, string matching, dynamic programming and NP-complete problems.


1501392                Practical Training - BI                                                                    (3-0:3)
Prerequisite: Completed 90 credit hours

Interns are expected to engage with industrial or governmental organizations in the Biomedical Informatics-related domains. The practical training is aimed at enhancing students' employability, technical and hands-on experience, providing the students with real-world experience of Biomedical Informatics Systems in real work environment business competencies. The trainees' mission is to monitor and practice all technical and admin activities related to the job performed. Students are expected to identify technical and soft skills gaps and work to improve their skills. Students are also expected to document their weekly activities to be composed in a final written report covering their practical learning experience. Students are expected to assess the training organization and give their comments and feedback.

1501435                Practical Training - BI                                                                    (3-0:3)
Prerequisite: 1501332 ML for Bioinformatics, 1501371 Design & Analysis of Algorithms

This course will introduce students to the basics of representing and acquiring digital images related to medical images. It will also cover the main medical image modalities including (Pathological, X-ray, CT, MRI, and ultrasound). Moreover, it will cover the current methods used to enhance and extract useful information from the medical images. Furthermore, using neural networks with medical image processing will also be introduced. Finally, a variety of medical images-based illness diagnostic scenarios will be presented.

1501391                Junior Project in Bioinformatics                                               (2-0:2)
Prerequisite: 1501318 Programming for Bioinformatics and 1450302 Bioinformatics, and 1501332 ML for Bioinformatics

The course serves as the first part of the one-year Senior Project in the BS Bioinformatics Program. Students work on a major bio informatics project integrating the knowledge gained from the courses in the curriculum. The project is team based. Students are expected to submit a proposal, followed by the detailed design of the project. Students are expected to create a working prototype of a bioinformatics system and write a comprehensive project report. At the end, students present the current status of the project, demo the prototype, and submit the final report. The main implementation of the project will continue in the Senior Project in Bioinformatics course.

1501497                Senior Project in Bioinformatics                                              (2-0:2)
Prerequisite: 1501391 Junior Project in Bioinformatics

This course is a continuation of the 1514391 Junior Project in Bioinformatics. Student will finalize the Bioinformatics project started in the previous semester. All projects are group projects. The students will submit two progress reports detailing the work done during the project. At the end students submit a comprehensive project report, and a poster to highlight the project. Students will also present the project in the form of an oral presentation in front of the faculty members and general audience. They will also do a live demonstration of the project after the presentation.


Core Electives

Descriptions of the Biomedical Informatics program core electives are given below.

1501341                Web Programming                                                                         (3-0:3)
Prerequisite: 1501116 Programming I

Introduction to HyperText Markup Language (HTML5): Tags, headers, text style, fonts, line breaks, rules, linking, images, lists, tables, forms, and frames. Semantic tags, Canvas, Geolocation, JQuery, Drag and Drop. Dynamic HTML: Cascading Style Sheets: Inline styles, external style sheets, backgrounds, positioning elements, text flow and box model. Filters: Flip, grayscale, sepia, saturate, hue-rotate, invert, opacity, blur, brightness, contrast, drop-shadow. JavaScrip: A simple program, memory concepts, assignment operators, decision making, control structures, if-else, while, repetition, for, switch, do/while, functions, arrays. Object Model and Collections: all, children. Event Model: OnClick, OnLoad, OnError, OnMouseMove, OnMouseOver, OnMouseOut, OnFocus, OnBlur, OnSubmit, OnReset. Multimedia. DHTMLMenu builder. PHP and databases.

1501352                Operating Systems                                                                        (3-0:3)
Prerequisite: 1501215 Data Structures

This course covers the history of operating systems. Processes: IPC, process scheduling, process synchronization, and deadlock. I/O: principles of I/O hardware and software, disks, and clocks. Memory management: Swapping, paging, virtual memory, and page replacement algorithms. File systems: Examples of some popular operating systems such as Unix, Linux, and Windows. 

1501365                Advanced Database Systems                                                     (3-0:3)
Prerequisite: 1501263 Introduction to Database Management Systems

This course will build on the concepts introduced in 1501263. The students will be exposed to more advanced topics and implementation related aspects of database management systems such as object databases, XML data querying, file structures, indexing, query optimization, transaction processing, concurrency control, and database recovery.


1501452                Introduction to IoT System                                                        (3-0:3)
Prerequisite: 1501250 Networking Fundamentals

The course teaches the background, origins and landscape of the Internet of Things (IoT). The course introduces the students to key IoT technologies, IoT architectures and IoT data management & security. It also teaches the concept of smart cities and demonstrates different examples of IoT use cases.


1501454               Cloud Computing                                                                          (3-0:3)
Prerequisite: 1501215 Data Structures

This course introduces students to widely used parallel and distributed techniques and applications of cloud computing – including the related state-of-the-art technologies, algorithms and tools. It allows students to develop understanding of the advanced cloud-based software development skills and to combine their existing and new skills in a real-life large-scale distributed business context.

1501455               Database Security                                                                         (3-0:3)
Prerequisite: 1501263 Introduction to Database Management System and 1501459 - Information Security

This course covers various topics in the arena of database security starting with the basics of information security and databases and delving deep into the field covering various topics including securing databases when stored at a network site, data management technologies, securing distributed database systems (including heterogenous and federated flavors), auditing and testing.


1501457               Data Hiding                                                                     (3-0:3)
Prerequisite: 1501215 - Data Structures and 150352 - Operating Systems

This course introduces fundamental concepts and methods used in information hiding. Topics include: data hashing and fingerprinting, steganography and steganographic security fundamentals, steganalysis, watermarking, entropy and redundancy, data hiding techniques in images, data hiding applications including biomedical applications, evaluation and testing of data hiding systems.


1501459               Information Security                                                                   (3-0:3)
Prerequisite: 1501215 Data Structures

Definition of Computer Security, CIA and DAD Triads. Access Control Methodologies, Subjects and Objects, Access Control Models. Security Policies, Security Administration Tools. Handling Security Incidents, Common Types of Attacks. Firewall Security, Perimeter Security Devices, Types of Firewalls. Network and Server Attacks and Penetration, Phases of Control, Methods of Taking Control. Cryptology, Secret-Key Cryptography, Bit Generators, History of ciphers, Data Encryption Standard, Advanced Encryption Standard. Number Theory, Primality, Integer Factorization, Congruence, Hash Functions. Public-Key Cryptography, trapdoor one-way functions, Secure Key-Exchange Protocol, different Cryptosystems, Digital Signatures, Database Security, Secret Sharing Scheme. 


1501490                Topics in Computer Science I                                                     (3-0:3)
Prerequisite: 1501215 Data Structures, or 1501214 Programming With Data Structures

This course involves special topics in Computer Science. The course usually introduces advanced/specialized areas that are not currently offered as regular courses in the computer Science curri­cula. The topic depends on the interest of the instructor and those of the senior students.


1501491                Topics in Computer Science II                                                    (3-0:3)
Prerequisite: 1501215 Data Structures, or 1501214 Programming With Data Structures

This course involves special topics in Computer Science. The course usually introduces advanced/specialized areas that are not currently offered as regular courses in the computer Science curri­cula. The topic depends on the interest of the instructor and those of the senior students. ​