The divergence of ASIC designs makes it difficult to run commonly used modern sequencing analysis pipelines due to software ...

Programming Background: The course involves solving programming assignments in Python. You must be comfortable with Python programming. This includes basic control structures in Python: conditional ...

Note: This course description is only applicable for the Computer Science Post-Baccalaureate ... divide and conquer algorithms, greedy algorithms, dynamic programming, linear programming, graph ...

Algorithm design and analysis is fundamental to all areas of computer science and gives a rigorous framework ... divide and conquer, dynamic programming, network flows, reductions, and randomized ...

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

The students are encouraged to think and use their acquired knowledge of algorithms in practical and highly applicable programming exercises. The Dynamic Programming and Optimal Control class focuses ...

Although the computer science principles behind ... Before BLAST, alignment programs used dynamic programming algorithms, such as the Needleman-Wunsch and Smith-Waterman algorithms, that required ...

Frequently used techniques include dynamic programming, reductions ... I mostly teach advanced computer science courses on algorithms and on bioinformatics. I am leading a research group on ...