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:

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.

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.​

Study Plan

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. ​