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INTRODUCTION TO BIOINFORMATICS

BMI/COMPSCI 576
과목 설명

Algorithms for computational problems in molecular biology. Studies algorithms for problems such as: genome sequencing and mapping, pairwise and multiple sequence alignment, modeling sequence classes and features, phylogenetic tree construction, and gene-expression data analysis.

선수과목

(COMPSCI 320 or COMPSCI 400 ) and MATH 222 , graduate/professional standing, or declared in the Capstone Certificate in Computer Sciences for Professionals

충족 요건

This course does not satisfy any prerequisites.

학점

미보고

개설 시기

미보고

평점
3.27

3.08% 과거 데이터 대비

수료율
95.71%

3.73% 과거 데이터 대비

A 비율
32.86%

-19.77% 과거 데이터 대비

학급 규모
70

35.16% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

COMPUTATIONAL NETWORK BIOLOGY

BMI/COMPSCI 775

Introduces networks as a powerful representation in many real-world domains including biology and biomedicine. Encompasses theory and applications of networks, also referred to as graphs, to study complex systems such as living organisms. Surveys the current literature on computational, graph-theoretic approaches that use network algorithms for biological modeling, analysis, interpretation, and discovery. Enables hands-on experience in network biology by implementing computational projects.

STATISTICAL METHODS FOR MOLECULAR BIOLOGY

BMI/STAT 877

Statistical and computational methods in statistical genomics for human and experimental populations. Review methods for quality control, experimental design, clustering, network analysis, and other downstream analysis of next-generation sequencing studies along with methods for genome wide association studies.

ADVANCED BIOINFORMATICS

BMI/COMPSCI 776

Advanced course covering computational problems in molecular biology. The course will study algorithms for problems such as: modeling sequence classes and features, phylogenetic tree construction, gene-expression data analysis, protein and RNA structure prediction, and whole-genome analysis and comparisons.

GENERAL BIOINFORMATICS FOR MICROBIOLOGISTS

MICROBIO 357

Provides foundational introduction to bioinformatics for microbiologists. Emphasis on the basic understanding of bioinformatics tools, analysis, and databases and their applications (e.g. Sequence alignment, Phylogenetic trees, Genome analyses). Topics include: command line manipulation, sequence alignment, file formats, phylogenetic trees, standard genome and protein databases, interpretation of microbial and viral genomes, and basic scientific computer programming.

PYTHON FOR BIOINFORMATICS

ABT 730

Introduce diverse strategies for computational analysis of macromolecular data using Python including sequence alignment, genome annotation, data retrieval from databases, phylogenetic analysis, and molecular evolution. Experiential learning is emphasized; confidence in practical skills is developed through persistent application of course content to projects focused on current problems in bioinformatic research.