المواد الدراسية
Research interest:
Bioinformatics:
My main research interest lies in facilitating the integration of experimental and computational research, in particular computational genomics and metagenomics. Genome projects as well as metagenomic projects...
Course description:
Abstract Data Types; Performance Measurement: Time & Space Complexity, Big-O notation. Basic Data Structures: Lists, Stacks, Queues, Priority Queues. Trees: Recursion, Terminology, General Trees, Binary Trees, Balanced Search...
Course Description
Bioinformatics is a rapidly evolving field that studies biological systems and biological data (such as DNA/protein sequences, macromolecular structures and functional genomics data) using analytic theory and practical tools of...
Course Description
Bioinformatics is a rapidly evolving field that studies biological systems and biological data (such as DNA/protein sequences, macromolecular structures and functional genomics data) using analytic theory and practical tools of...
Schedule and Office Hours
Classes: Monday at 13:00 - 14:50 and Wednesday at 13:00-13:50 in A 011 1 31 0160
Exercises: Wednesday at 14:00 - 14:50 in A 011 1 31 0160
Office Hours:
Sundays,Tuesdays from 8am to 11am and Wednesdays from 8am to 12 pm....
Annoucements:
18/9/2016: Groups are assigned. Please meet with your supervisors as soon as possible
The deadlines for 496 spring 2016 are as follows
Abstract ,2016
Midterm report , 2016
Final...
Course Objectives
This course aims at improving the OO design skills of the students by understanding the following concepts:
Relationships: Association, Aggregation, Composition.
Inheritance and dynamic binding and polymorphism.
Exception...
Course Objective
The objective of this course is to develop the students' ability to use basics of procedural programming. The students learn the main features of procedural programming: control structures, functions, arrays, c-style strings,...
Course Objective
This course covers the theory and practice of machine learning from a variety of perspectives (including Design, analysis, implementation and applications of learning algorithms). The course covers theoretical concepts such as...
Course Objective:
Understanding the main characteristics of distributed systems and the various design choices required for building a distributed system such as: the architectural models varying from client/server to peer-to-peer, grid-computing;...