DEPARTMENT OF COMPUTER AND INFORMATION SCIENCES POSTGRADUATE ACADEMIC PROGRAMME FOR BIO-INFORMATICS


Table of Contents


Vision of the University

To be a leading World-Class Christian Mission University, committed to raising a new generation of leaders in all fields of Human endeavour.

Mission of the University

To create knowledge and restore the dignity of the black man via a Human Development and Total Man Concept driven curriculum employing innovative, leading edge, teaching and learning methods, research and professional services that promote integrated, life-applicable, life-transforming education relevant to the context of Science, Technology and Human Capacity Building.

History of the Department and its Postgraduate Programmes

The Department of Computer and Information Sciences began with two programmes: Computer Science and Management Information System in the year 2002. The full accreditation by NUC teams of its two programmes took place in the year 2005 and 2007 respectively.

The School of Postgraduate Studies was established to meet an important manpower need of the University. To train (at the first instance) Covenant University Faculty without Ph.D. degrees. It admitted its first set of students in December 2003. This ushered in the first phase of the School. During this phase, the School’s facilities are devoted exclusively to training the University’s staff and building a solid research base.

All postgraduate programmes of the department provide in-depth skills that enable students develop real practical skills, in research, system or application design, and implementation. The M.Sc./M.Phil. degree in Computer Science,  and M.Sc./M.Phil. degree in Management Information System from Covenant University are challenging and rewarding, equipping students with more advanced knowledge and capacity for responsibilities in the academia or industry, also providing a sound basis for subsequent PhD study.

The Ph.D degree in Computer Science and Ph.D degree in Management Information System from Covenant University are research based and designed to equip students with the needed skills to pursue a rewarding career in the academics. All the programmes are designed to offer applications of core techniques and methods to challenging real-world problems, particularly in the area of Software Engineering, Bioinformatics, and Mobile Computing and Management Information Systems.

Philosophy

The philosophy of the department involves a broad strategy of human resources development that encompasses educational, cultural, social, political and spiritual development such that the graduates will be able to contribute to the building of national identity and integrity by being sufficiently creative and innovative to seek self-employment in the field of Information Technology and its allied disciplines, or in the least be immediately employable.

Objectives of Postgraduate Studies

  • To provide facilities for learning, to give instructions and training in such areas of knowledge as will produce sound and mentally equipped graduates who will provide intellectual leadership in academic institutions, industry, and public sector through the development of the “Total Man” approach.
  • To develop and offer academic and professional programmes leading to the award of diplomas, postgraduate research and higher degrees which emphasize planning, adaptive and technological maintenance, developmental and productive skills.
  • To promote by research and other means, the advancement of knowledge and its practical application to social, cultural, economic, scientific and technological problems.
  • To encourage and promote scholarship and conduct research in all fields of learning and human endeavour.
  • To disseminate scientific and technological knowledge among scientist, researchers, industries, trade services and other bodies.
  • To relate its activities to the technological, scientific and socio-economic needs of the people of Nigeria and to undertake other activities appropriate for a University of the highest standard.

Types of Programme

The department offers courses and research leading to the award of the following degrees:-

  1. Master of Science degree in Computer Science
  2. Master of Science degree in Management Information Systems
  3. Doctor of Philosophy in Management Information Systems
  4. Doctor of Philosophy in Computer Science

The available specializations at the three levels are:

  1. Software Engineering
  2. Management Information system
  3. Bioinformatics

Master of Science in Bio-informatics

Admission Requirements

A candidate with a first degree in Computer Science from a recognised University with minimum of a second-class lower division may be admitted provided the University matriculation requirement is satisfied.

Award of Degree

To be eligible for the award of an M.Sc. in Computer Science, a candidate must satisfactorily and successfully complete the course work (32 units), pass all the prescribed examinations and successfully defend a dissertation based on the candidate’s project.

Curriculum
Alpha
semester
Course Code Course Title

Units

Bioinformatics option compulsory courses

CIS811 Advanced Analysis and Design of Computer Programs

3

CIS812 Advanced Operating System and Computer Architecture

3

CIS814 Software Design Techniques and Tools

3

CIS815 Compiler Design

3

CIS816 Bioinformatics I

3

University Courses compulsory Courses

TMC811 Total Man Concept

1

EDS811 Entrepreneurial Studies

1

SUB-TOTAL

17

Omega
Semester
Course Code Course Title

Units

 

Bioinformatics Option compulsory courses

CIS822 Advanced Computational Geometry

3

CIS823 Internet Programming and Web Application Management

3

CIS824 Artificial Intelligence

3

CIS826 Bioinformatics II

3

CIS827 Stochastic Processes

3

 

General courses compulsory courses

CIS899 Research Project

6

  SUB-TOTAL

21

TOTAL

38

 

COURSE DESCRIPTION
Alpha Semester

CIS 811 Advanced Analysis and Design of Computer Programs
Techniques of analyzing upper bounds and lower bounds for algorithms. Searching, Sorting, Data Structure: Arrays, Pointers, List, ADI Trees, Binary trees, Simulated  annealing, Balanced tree, Multi- Search tree, B-tree, B*-tree, B** – tree, B*** -tree, R-tree, Hashing techniques, graph theory, Dynamic programming, Combinatorial algorithms, approximation, branch-and-bound, divide-and-conquer, dynamic programming, greedy algorithms, and randomization applied to polynomial and NP- hard problems.

CIS 812 Advanced Operating Systems and Computer Architecture
Advanced concepts in operating systems, inter-process communication and synchronization, distributed operating systems (concurrent process, design techniques), file system, memory management, deadlock, protection and security, case studies from Linux, MACH, XP, Technology and Architecture(the effects of technological change on cost, and complexity), the CPU design, memory hierarchies, I/O processors, pipeline design, RISC architecture, multiple instruction stream(MIMD), and single instruction stream with multiple data stream (SIMD), multiprocessors design and structure (bus-based systems, cube systems and switching network systems).The era of supercomputers, array processors and transporters.

CIS 814 Software Design Techniques and Tools
The Object Model. Software Complexity and the Object Oriented (O,O) paradigm, Abstraction, Encapsulation and Information Hiding. Inheritance and Polymorphism. Object Communication Model. Classification and Object Identification. Object-Based Modular Decomposition. Concurrent Objects. Object Interface Specification. Design patterns. Static and Dynamic Models. Architectural Design. Reusable Objects. Design Evolution. Distributed Object Architectures. O.O. Databases. O.O. Software Metrics. Competing Methodologies. Benefits and Risks of O.O. Development UML notation and diagrams. Application and Case Studies.

CIS 815 Compiler Design
An introduction to the major methods used in compiler implementation.  The parsing methods of LL(K) and LR(K) are to be covered as well as finite state methods for lexical analysis, symbol table construction, internal forms for a program, runtime storage management for block structured languages and an introduction to code optimization.

CIS 816 Bioinformatics I
Basic concepts of molecular biology, importance of bioinformatics, pair-wise sequence alignment (dynamic programming, heuristic methods and similarity matrices), multiple sequence alignment, BLAST, FASTA, hidden Marker Module (CMM) ( Construction, application in alignment and gene prediction), phylogenetic, tree, fragment assembly, physical mapping, combinatoric application in sequencing, sequence analysis and annotating, genomic rearrangements, computational gene finding.

Omega semester

CIS 822 Advanced Computational Geometry
Computational Geometry, line segment intersection, polygon triangulation (guarding an art gallery), linear programming (manufacturing with mfolds), orthogonal range searching (querying a database), point location, voronoi diagrams (the post office problem), arrangements and duality (supersampling in ray tracing), delaunay triangulation, more geometric data structures, covex hulls, binary space partitions (the painter’s algorithm), robot motion planning, quadtrees (non-uniform mesh generation), visibility graphs (finding the shortest route), and simplex range searching.

CIS 823: Internet Programming and Web Application Management 
INTERNET: Definition, architecture, services, Internet addressing. Internet protocol, IPv4, IPv6. Internet and Mobile programming, System administration, and security issues. Webpage Basics: Links, Lists, Tables, Multimedia: Graphics, Audio, Video, Enhanced Features: Image Maps, Counters, User Interaction: Forms, CGI, PERL, Java, Design Considerations, Dynamic Webpages, Active Server Page. Wireless Networks: WLAN, WWAN, Mobile Computing, 802.11 standards and generations (1, 2, 2.5, and 3G). ML, WML, WAP-enabled databases, Wireless Mobile Technologies: The mobile Internet, WAP, i-Mode, HDML, Bluetooth, and WML scripts.

CIS 824 Artificial Intelligence (AI) 
What is AI, AI problems, AI techniques, problem spaces, searching techniques, Heuristic search Techniques: Hill Climbing, Best-First-Search, Tabu search, Simulated Annealing, Approaches to knowledge representation, statistical reasoning: Bayesian networks, fuzzy logic, machine learning, Game playing: minimax search procedure, Alpha-Beta cutoffs, iterative deepening, opponent – model, Nash equilibrium, References on specific games: prisoners dilemma, chess, draught, Ayo.

CIS 826 Bioinformatics II
RNA secondary structure prediction, protein homology modeling, protein threatening, protein molecular dynamic, protein as initial structure prediction, integration of molecular biology data banks, experimentation biology support (sequence, structure prediction, DNA arrays etc)

CIS 827 Stochastic Processes
Stochastic Process: Poison Processes and Markov Chains, The Homogeneous Poisson Process and the Poisson distribution, The Poison and the Binomial Distributions, The Poison and the Gamma Distributions, Introduction to finite Markov Chains, Transition Probabilities and the Transition Probability Matrix, Markov Chains with Absorbing states, Markov chains with No Absorbing states, The Graphical Representation of a Markov chain, The Graphical representation of a Markov chain, Modeling. Random Walks, Introduction  The Simple Random Walk, The difference Equation Approach, The Moment – Generating function Approach, General Walks, General Walks: Asymptotic theory. Markov Chains: Introduction, Markov chains with no Absorbing States, Higher-Order Markov Dependence, Patterns in sequences with first- order Markov Dependence, Markov chains Monte carlo, Markov chains with Absorbing states, Continuous -Time Markov Chains.

CIS 899 Dissertation
A student applies different computer algorithms and methodologies to one of the research oriented real life problems. The student should choose one area of computer applications that is related to his area of specialization.

Master of Philosophy (M. Phil.) in Bio-informatics

Admission Requirements

A candidate with a good Masters degree with coursework and project dissertation thesis with a CGPA below 3.50 from a recognized university may be admitted provided the university matriculation requirement is satisfied.

Award of Degree

To be eligible to proceed to the Master of Philosophy programme of the Department, a candidate must successfully complete the course work, pass all the prescribed examinations and successfully defend a dissertation.

Curriculum
Alpha
semester
Course Code Course Title

Units

Bioinformatics option compulsory courses

CIS911 Advanced Analysis and Design of Computer Programs

3

CIS912 Advanced Operating System and Computer Architecture

3

CIS914 Software Design Techniques and Tools /td>

3

CIS916 Bioinformatics I&II

3

University Courses compulsory Courses

TMC811 Total Man Concept

1

EDS811 Entrepreneurial Studies

1

SUB-TOTAL

14

Omega
Semester
Course Code Course Title

Units

 

Bioinformatics Option compulsory courses

CIS922 Advanced Computational Geometry

3

CIS923 Internet Programming and Web Application Management

3

CIS924 Cluster and Grid Computing

3

CIS924 Engineering of Intelligent Software Systems

3

 

General courses compulsory courses

CIS999 Research Project

6

  SUB-TOTAL

18

TOTAL

32

 

COURSE DESCRIPTION
Alpha Semester

CIS 911 Advanced Analysis and Design of Computer Programs
Techniques of analyzing upper bounds and lower bounds for algorithms. Searching, Sorting, Data Structure: Arrays, Pointers, List, ADI Trees, Binary trees, Simulated  annealing, Balanced tree, Multi- Search tree, B-tree, B*-tree, B** – tree, B*** -tree, R-tree, Hashing techniques, graph theory, Dynamic programming, Combinatorial algorithms, approximation, branch-and-bound, divide-and-conquer, dynamic programming, greedy algorithms, and randomization applied to polynomial and NP- hard problems.

CIS 912 Advanced Operating Systems and Computer Architecture
Advanced concepts in operating systems, inter-process communication and synchronization, distributed operating systems (concurrent process, design techniques), file system, memory management, deadlock, protection and security, case studies from Linux, MACH, XP, Technology and Architecture(the effects of technological change on cost, and complexity), the CPU design, memory hierarchies, I/O processors, pipeline design, RISC architecture, multiple instruction stream(MIMD), and single instruction stream with multiple data stream (SIMD), multiprocessors design and structure (bus-based systems, cube systems and switching network systems).The era of supercomputers, array processors and transporters.

CIS 914 Software Design Techniques and Tools
The Object Model. Software Complexity and the Object Oriented (O,O) paradigm, Abstraction, Encapsulation and Information Hiding. Inheritance and Polymorphism. Object Communication Model. Classification and Object Identification. Object-Based Modular Decomposition. Concurrent Objects. Object Interface Specification. Design patterns. Static and Dynamic Models. Architectural Design. Reusable Objects. Design Evolution. Distributed Object Architectures. O.O. Databases. O.O. Software Metrics. Competing Methodologies. Benefits and Risks of O.O. Development UML notation and diagrams. Application and Case Studies.

CIS 916  Bioinformatics I
Basic concepts of molecular biology, importance of bioinformatics, pair-wise sequence alignment ( dynamic programming, heuristic methods and similarity matrices), multiple sequence alignment, BLAST, FASTA, hidden Marker Module (CMM) ( Construction, application in alignment and gene prediction), phylogenetic, tree, fragment assembly, physical mapping, combinatoric application in sequencing, sequence analysis and annotating, genomic rearrangements, computational gene finding.

Omega Semester

CIS 921 Cluster and Grid Computing 
The purpose of the course is to provide basic knowledge on the most important principles, methods, tools, systems, standards, etc. behind cluster and grid technologies. Introduction to distributed and high-performance computing. Basic terms: distributed computing, HPC, HPCC, network computing, Internet computing, cluster, grid, meta-computing, middleware, etc; milestones of the history, some representative applications; Classification: Taxonomies, MPP, SMP, CC-NUMA, cluster: dedicated high performance (HP), high availability (HA), CoPs, PoPs, CoWs; distributed, on-demand, high-throughput, collaborative, data-intensive computing; Basics of communication media and protocols: TCP/IP, Internet2, QoS, ATM, Fast Ethernet, etc.; Programming models: Message passing, client-server, peer-to-peer, broker computing, code shipping, proxy computing, mobile agents. Toolkit and OO systems; Higher level communication: Light-weight communication, sockets, standard APIs, active messages; Storage and file problems: Network RAM, RAID and software RAID. Distributed File systems: NFS, AFS, OSF-DSF, RSF; Message passing standards: PVM (Parallel Virtual Machine), MPI (Message Passing Interface); Object-oriented de facto standards CORBA and DCOM; Java-based methods: JVM, RMI, Bytecode, Applet and Servlet, JavaBean and JavaSpaces, Jini; Grid toolkit approach: Globus Hourglass concept, communication, resource and process management, data access, security; Object-oriented approach: Legion Language support, component wrapping, program support, resource management; Security: Confidentiality, integrity and availability. Authentication, authorization, assurance, auditing, accounting; scheduling: Algorithms, policies and techniques, high performance and high throughput schedulers, resource scheduling; Grid monitoring: Tasks, types, architecture, components. The course requires a student presentation on a selected topic by each participant. Students are provided by a reading list and copies of slides presented at the lectures in PDF or PS format. The course is aimed at bridging the gap between the distributed and high performance topics in computer science and engineering university education and the current hot research topics and activities of the field.

CIS 922 Advanced Computational Geometry
Computational Geometry, line segment intersection, polygon triangulation (guarding an art gallery), linear programming (manufacturing with mfolds), orthogonal range searching (querying a database), point location, voronoi diagrams (the post office problem), arrangements and duality (supersampling in ray tracing), delaunay triangulation, more geometric data structures, covex hulls, binary space partitions (the painter’s algorithm), robot motion planning, quadtrees (non-uniform mesh generation), visibility graphs (finding the shortest route), and simplex range searching.

CIS 923: Internet Programming and Web Application Management
INTERNET: Definition, architecture, services, Internet addressing. Internet protocol, IPv4, IPv6. Internet and Mobile programming, System administration, and security issues. Webpage Basics: Links, Lists, Tables, Multimedia: Graphics, Audio, Video, Enhanced Features: Image Maps, Counters, User Interaction: Forms, CGI, PERL, Java, Design Considerations, Dynamic Webpages, Active Server Page. Wireless Networks: WLAN, WWAN, Mobile Computing, 802.11 standards and generations (1, 2, 2.5, and 3G). ML, WML, WAP-enabled databases, Wireless Mobile Technologies: The mobile Internet, WAP, i-Mode, HDML, Bluetooth, and WML scripts.

CIS 924 Engineering of Intelligent Software Systems
Introduction
It is becoming even more common that software-based system includes some form of “intelligent” (adaptive, reasoning, etc.) software. In addition, there is a clear tendency that such systems are getting more distributed (cf. Ambient Intelligence, Pervasive Computing, and Ubiquitous Computing). In order to develop the software for this type of systems, a wide knowledge of existing algorithms, methods, and technologies is desired. The idea behind the Intelligent Software Systems program is to provide a set of courses that together satisfy this demand.
Aim
The goal is to give the students a broad view of the area of intelligent software systems including: algorithms, technologies, and methodologies for developing intelligent (distributed) software systems. In addition, the aim is to provide an introduction to research methodology in both theory and practice.
Course Outline
Knowledge Engineering, Ontologies, Semantic Web Services, Applied Artificial Intelligence, Middleware Technologies, Evolutionary Computation, Neural Networks, Machine Learning, Software Agent Systems, Optimisation Techniques, Hybrid Intelligent Systems, Decision Support Systems (Fuzzy Logic and Fuzzy Expert Systems, CBR systems, Recommender Systems), Engineering of Internet Applications, Natural Language Processing & Applications, Human Computer Interaction , Automated Software Engineering, Automatic Verification, Intelligent Security Systems, Safety Critical Systems & Software Reliability, Formal Methods.

CIS 926 Bioinformatics II
RNA secondary structure prediction, protein homology modelling, protein threatening, protein molecular dynamic, protein as initial structure prediction, integration of molecular biology data banks, experimentation biology support (sequence, structure prediction, DNA arrays etc)

CIS 999 Dissertation 
A student applies different computer algorithms and methodologies to one of the research oriented real life problems. The student should choose one area of computer applications that is related to his area of specialization.

Doctor of Philosophy in Bio-informatics

Admission Requirements

A candidate with a good Masters degree in Computer Science, with coursework and project dissertation, and a minimum grade of 60% (or a CGPA of 3,50) from a recognized University may be admitted provided the university matriculation requirement is satisfied.

Award of Degree

To be eligible for the award of a Ph.D in Computer Science, a candidate must successfully complete the course work, pass all the prescribed examinations and successfully defend a thesis based on the candidate’s project.

Curriculum
Alpha
semester
Course Code Course Title

Units

 

Bioinformatics Option compulsory courses

CIS931 Cluster and Grid Computing

3

CIS932 Engineering of Intelligent Software Systems

3

CIS935 Computational Molecular Biology

3

CIS926 Writing Technical Report and Current Topics in Computing

3

TMC811 Total Man Concept

1

EDS811 Entrepreneurial Studies

1

TOTAL CREDITS

14

COURSE DESCRIPTION

CIS 931: Cluster and Grid Computing
The purpose of the course is to provide basic knowledge on the most important principles, methods, tools, systems, standards, etc. behind cluster and grid technologies.

Course Outline:

Introduction to distributed and high-performance computing. Basic terms: distributed computing, HPC, HPCC, network computing, Internet computing, cluster, grid, meta-computing, middleware, etc; milestones of the history, some representative applications; Classification: Taxonomies, MPP, SMP, CC-NUMA, cluster: dedicated high performance (HP), high availability (HA), CoPs, PoPs, CoWs; distributed, on-demand, high-throughput, collaborative, data-intensive computing; Basics of communication media and protocols: TCP/IP, Internet2, QoS, ATM, Fast Ethernet, etc.; Programming models: Message passing, client-server, peer-to-peer, broker computing, code shipping, proxy computing, mobile agents. Toolkit and OO systems; Higher level communication: Light-weight communication, sockets, standard APIs, active messages; Storage and file problems: Network RAM, RAID and software RAID. Distributed File systems: NFS, AFS, OSF-DSF, RSF; Message passing standards: PVM (Parallel Virtual Machine), MPI (Message Passing Interface); Object-oriented de facto standards CORBA and DCOM; Java-based methods: JVM, RMI, Bytecode, Applet and Servlet, JavaBean and JavaSpaces, Jini; Grid toolkit approach: Globus Hourglass concept, communication, resource and process management, data access, security; Object-oriented approach: Legion Language support, component wrapping, program support, resource management; Security: Confidentiality, integrity and availability. Authentication, authori-zation, assurance, auditing, accounting; scheduling: Algorithms, policies and techniques, high performance and high throughput schedulers, resource scheduling; Grid monitoring: Tasks, types, architecture, components.

The course requires a student presentation on a selected topic by each participant. Students are provided by a reading list and copies of slides presented at the lectures in PDF or PS format. The course is aimed at bridging the gap between the distributed and high performance topics in computer science and engineering university education and the current hot research topics and activities of the field.

CIS 932: Engineering of Intelligent Software Systems
Introduction
It is becoming even more common that software-based system includes some form of “intelligent” (adaptive, reasoning, etc.) software. In addition, there is a clear tendency that such systems are getting more distributed (cf. Ambient Intelligence, Pervasive Computing, and Ubiquitous Computing). In order to develop the software for this type of systems, a wide knowledge of existing algorithms, methods, and technologies is desired. The idea behind the Intelligent Software Systems program is to provide a set of courses that together satisfy this demand.

Aim
The goal is to give the students a broad view of the area of intelligent software systems including: algorithms, technologies, and methodologies for developing intelligent (distributed) software systems. In addition, the aim is to provide an introduction to research methodology in both theory and practice.

Course Outline
Knowledge Engineering, Ontologies, Semantic Web Services, Applied Artificial Intelligence, Middleware Technologies, Evolutionary Computation, Neural Networks, Machine Learning, Software Agent Systems, Optimisation Techniques, Hybrid Intelligent Systems, Decision Support Systems (Fuzzy Logic and Fuzzy Expert Systems, CBR systems, Recommender Systems), Engineering of Internet Applications, Natural Language Processing & Applications, Human Computer Interaction , Automated Software Engineering, Automatic Verification, Intelligent Security Systems, Safety Critical Systems & Software Reliability, Formal Methods.

CIS 935 Computational Molecular Biology
Basic concepts of molecular biology, importance of bioinformatics, pair-wise sequence alignment ( dynamic programming, heuristic methods and similarity matrices), multiple sequence alignment, BLAST, FASTA, hidden Marker Module (CMM) ( Construction, application in alignment and gene prediction), phylogenetic, tree, fragment assembly, physical mapping, combinatoric application in sequencing, sequence analysis and annotating, genomic rearrangements, computational gene finding. RNA secondary structure prediction, protein homology modeling, protein threatening, protein molecular dynamic, protein as initial structure prediction, integration of molecular biology data banks, experimentation biology support (sequence, structure prediction, DNA arrays etc).

CIS 936 : Writing Technical Report and Current Topics in Computing
A review of current work and theories in computing.  Emphasis on latest work and theories in Software Engineering, Bioinformatics, Mobile Computing, Networking, Management Information System etc.  Each student is expected to present a seminar on any chosen topic.
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