Degree Structure
College
Computing and Informatics
Department
Computer Science
Level
Undergraduate
Study System
Courses
Total Credit Hours
124 Cr. Hrs.
Duration
4 Years
Intake
Fall and Spring
Language
English
Study Mode
Full Time
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Degree Overview
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.
What You Will Learn
You have chosen the field of Biomedical Informatics; thus, you will be 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 program helps you to develop a solid technical foundation in Biomedical Informatics and to become an informatics leader in the bioinformatics, pharmaceutical, clinical, or healthcare industries.
University Requirements
College Requirements
Degree Requirements
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) | |||
| - | UR | PR | Total |
| Mandatory Core Credits | 18 | 91 | 109 |
| Support Credits | - | - | - |
| Electives Credits | 6 | 9 | 15 |
| Total | 24 | 100 | 124 |
Mandatory Core Courses
This set consists of 91 credit hours listed below.
| Course # | Course Title | Cr. Hr. | Prerequisite |
| 0900101 | Human Biology 1 | 3 | None |
| 0900307 | Introduction to Systems Biology Modelling | 3 | None |
| 0900324 | Biomedical Ethics | 1 | None |
| 0900409 | Computational Genomics | 3 | 1501332, 1501364 |
| 0900412 | Statistical Genomics | 3 | 1440281 |
| 1420101 | General Chemistry (1) | 3 | None |
| 1420102 | General Chemistry (1) Lab | 1 | 1420101 |
| 1430113 | Physics for Medical Sciences | 3 | None |
| 1440131 | Calculus I | 3 | None |
| 1440211 | Linear Algebra I | 3 | 1440131 |
| 1440281 | Intro Probability & Statistics | 3 | 1440131 |
| 1450101 | General Biology 1 | 3 | None |
| 1450102 | General Biology 2 | 3 | 1450101 |
| 1450107 | General Biology Lab | 1 | 1450101 |
| 1450302 | Bioinformatics | 3 | 1501116 |
| 1450303 | Bioinformatics Lab | 1 | 14503202 |
| 1450341 | Molecular Genetics | 3 | 1450102 |
| 1450453 | Protein Biotechnology & Eng. | 3 | 1450102 |
| 1501116 | Programming I | 4 | None |
| 1501211 | Programming II | 3 | 1501116 |
| 1501215 | Data Structures | 3 | 1501211 |
| 1501250 | Networking Fundamental s | 3 | 1501215 |
| 1501263 | Intro. to Database Management System | 3 | 1501215 |
| 1501279 | Discrete Structures | 3 | 1440131 |
| 1501318 | Programming for Bioinformatics | 3 | 1501116 |
| 1501330 | Introduction to Artificial Intelligence. | 3 | 1501215 |
| 1501332 | Machine Learning for Bioinformatics | 3 | 1440131, 1440281, 1501215 |
| 1501364 | Big Data Analytics | 3 | 1501263, 1501318, 1440281 |
| 1501371 | Design & Analysis of Algorithms | 3 | 1501279, 1501215 |
| 1501391 | Junior Project in Bioinformatics | 2 | 1501318, 1450302, 1501332 |
| 1501392 | Practical Training - BI | 3 | Completion of 90 credits |
| 1501435 | Medical Image Processing | 3 | 1501332, 1501371 |
| 1501497 | Senior Project in Bioinformatics | 3 | 1501391 |
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 Title | Cr. Hr. | Prerequisite |
| 1427241 | Molecular Modelling | 3 | 1420101, 1420112, 1450453 |
| 1450250 | Molecular and Cell Biology | 3 | 1450102 |
| 1501341 | Web Programming | 3 | 1501116 |
| 1501352 | Operating Systems | 3 | 1501215 |
| 1501365 | Advanced Database System | 3 | 1501263 |
| 1501452 | Introduction to IoT Systems | 3 | 1501250 |
| 1501454 | Cloud Computing | 3 | 1501215 |
| 1501455 | Database Security | 3 | 1501263, 1501459 |
| 1501457 | Data Hiding | 3 | 1501215, 1501352 |
| 1501459 | Information Security | 3 | 1501215 |
| 1501490 | Topics in Computer Science I | 3 | 1501215 |
| 1501491 | Topics in Computer Science II | 3 | 1501215 |
| 1502201 | Digital Logic Design | 3 | 1501100 |
| 1502442 | Network Programming | 3 | 1502346, 1501116 |
Study Plan
| Year I, Semester 1 (16 Credits) | |||
| Course # | Title | Cr. Hr. | Prerequisites |
| 201102 | Arabic Language | 3 | - |
| 202112 | English for Academic Purposes | 3 | - |
| 1501100 | Intro. to IT(English) | 3 | - |
| 1440131 | Calculus I | 3 | - |
| 1450101 | General Biology 1 | 3 | - |
| 1450107 | General Biology Lab | 1 | 1450101 |
| Year I, Semester 2 (14 Credits) | |||
| Course # | Title | Cr. Hr. | Prerequisites |
| - | University Elective 1 | 3 | - |
| 1501116 | Programming I | 4 | - |
| 1440211 | Linear Algebra I | 3 | - |
| 1420101 | General Chemistry (1) | 3 | None |
| 1420102 | General Chemistry (1) Lab | 1 | 1420101 or 0215101 |
| Year 2, Semester 1 (18 Credits) | |||
| Course # | Title | Cr. Hr. | Prerequisites |
| 104100 | Islamic Culture | 3 | - |
| - | University Elective 2 | 3 | - |
| 1501211 | Programming II | 3 | 1501116 |
| 1450102 | General Biology 2 | 3 | 1450101 |
| 1501279 | Discrete Structures | 3 | 1440131 |
| 302200 | Fund. of Innovation & Entrepreneurship | 3 | - |
| Year 2, Semester 2 (18 Credits) | |||
| Course # | Title | >Cr. Hr. | Prerequisites |
| 204102 | UAE Society | 3 | - |
| 1501318 | Programming for Bioinformatics | 3 | 1501211 |
| 1501215 | Data Structures | 3 | 1501211 |
| 1440281 | Intro Prob. & Stat. | 3 | 1440131 |
| 900101 | Human Biology 1 | 3 | None |
| 1430113 | Physics for Medical Science | 3 | - |
| Year 3, Semester 1 (14 Credits) | |||
| Course # | Title | Cr. Hr. | Prerequisites |
| 1501263 | Intro. to DB Manag. Sys. | 3 | 1501215 |
| 900324 | Biomedical Ethics | 1 | - |
| 1501330 | Introduction to Artificial Intelligence | 3 | 1501215, 1501279 |
| 1501332 | ML for Bioinformatics | 3 | 1440131, 1440281, 1501215 |
| 1450302 | Bioinformatics | 3 | 1450102, 1501116 |
| 1450303 | Bioinformatics lab | 1 | - |
| Year 3, Semester 2 (17 Credits) | |||
| Course # | Title | Cr. Hr. | Prerequisites |
| 1501250 | Networking Fundamentals | 3 | 1501215 |
| 1501364 | Big Data Analytics | 3 | 1501263, 1501318, 1440281 |
| 1450341 | Molecular Genetics | 3 | 1450102 |
| 1501391 | Junior Project in Bioinformatics | 2 | 1501318, 145302, 1501332 |
| 1501371 | Design & Analysis of Algorithms | 3 | 1501279, 1501215 |
| 1501392 | Practical Training - BI | 3 | Completed 90 credit hours |
| Year 4, Semester 1 (15 Credits) | |||
| Course # | Title | Cr. Hr. | Prerequisites |
| 1501497 | Senior Project in Bioinformatics | 3 | 1501391 |
| 1501435 | Medical Image Processing | 3 | 1501332, 1501371 |
| 0900307 | Introduction to Systems Biology Modelling | 3 | - |
| - | Program elective 1 | 3 | - |
| - | Program elective 2 | 3 | - |
| Year 4, Semester 2 (12 Credits) | |||
| Course | Title | Cr. Hr. | Prerequisites |
| 0900409 | Computational Genomics | 3 | 1501332, 1501364 |
| 1450453 | Protein Biochemistry & Eng. | 3 | 1450102 |
| 0900412 | Statistical Genomics | 3 | - |
| - | Program Elective 3 | 3 | - |
Course Description
| Course # | Course Title | Credits |
| 1501100 | Introduction to IT (English) | (2-2:3) |
| 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. | ||
| Course # | Course Title | Credits |
| 1501116 | Programming I | (3-2:4) |
| 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. | ||
| Course # | Course Title | Credits |
| 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++). | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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 covers 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 1501391 | Junior Project in Bioinformatics | (2-0:2) |
| Prerequisite: 1501318 | Programming for Bioinformatics | - |
| 1450302 | Bioinformatics | - |
| 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 bioinformatics 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. | ||
| Course # | Course Title | Credits |
| 1501497 | Senior Project in Bioinformatics | (2-0:2) |
| Prerequisite: 1501391 | Junior Project in Bioinformatics | - |
| This course is a continuation of the 1501391 Junior Project in Bioinformatics. Students 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
| Course # | Course Title | Credits |
| 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. JavaScript: 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. DHTML Menu builder. PHP and databases. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 1501455 | Database Security | (3-0:3) |
| Prerequisite: 1501263 | Introduction to Database Management System | - |
| 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 heterogeneous and federated flavors), auditing and testing. | ||
| Course # | Course Title | Credits |
| 1501457 | Data Hiding | (3-0:3) |
| Prerequisite: 1501215 | Data Structures | - |
| 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. | ||
| Course # | Course Title | Credits |
| 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. | ||
| Course # | Course Title | Credits |
| 1501490 | Topics in Computer Science I | (3-0:3) |
| Prerequisite: 1501215 | Data Structures | - |
| 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. | ||
| Course # | Course Title | Credits |
| 1501491 | Topics in Computer Science II | (3-0:3) |
| Prerequisite: 1501215 | Data Structures | - |
| 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. | ||
Career Path
Graduates of the program can pursue diverse career paths, working in governmental agencies, private, and international organizations such as hospitals, medical centers, and healthcare insurance companies. They can hold positions ranging from research work at research institutes to software engineers at software companies, hospitals, pharmaceutical companies, and healthcare laboratories. Potential roles include clinical data managers, clinical systems analysts, consultants, researchers, developers, project supervisors/managers, or quality support analysts.
How will you make an impact?
Every student’s journey at UoS and beyond is different, which is why our Career & Professional Development team provides personalized career resources to help students make an impact for years to come.
