SUMMER TERM 2018


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CRN:
45433
Subj:
INFO
Num: 510
Title:
Programming with Biological Data
Level:
Graduate Non-Degree Graduate
Min Cr:
3
Schedule Type:
Lecture
Status:
Active
Instructor:
Malay K Basu / Alexander Rosenberg (P)


Description

This course provides students necessary bioinformatics programming and data skills using Linux, MySQL and R. Linux commands and use of scripting languages will be taught in the context of bioinformatics data processing. Basic and practical database skills will be covered. Basic statistics using R to conduct reproducible research will be taught. Students will learn homology search using BLAST, understand basic next-generation sequencing data processing and analysis pipeline development. The focus will be on practical bioinformatics concepts using scripting/programming applied to data analysis problems.

FALL TERM 2018


CRN: 62026

Subj: INFO
Num: 601
Title: Introduction to Bioinformatics
Level: Graduate Non-Degree Graduate
Min CR: 3
Schedule Type: Lecture
Status: Active
Instructor: Zechen Chong (P)

Description
Introduction to bioinformatics and computational biology, with emphasis on concepts and application of informatics tools to molecular biology. It covers biological sequence analysis, gene prediction, genome annotation, gene expression analysis, protein structure prediction, evolutionary biology and comparative genomics, bioinformatics databases, cloud computing, basic R-based data analysis, simple programming skills using Perl, Linux/Unix environment and command lines, visual analytics, and social/legal aspects of open science. It will have a class research project component.

CRN: 62054
Subj: INFO
Num: 612
Title: Biomedical Informatics Research 
Level: Graduate Non-Degree Graduate
Min CR: 3
Schedule Type: Lecture
Status: Active
Instructor: Alexander Rosenberg (P)


Prerequisites
Graduate level INFO 603 Minimum Grade of C

Description
In this course, we will explore the use of visualization techniques as a concise and effective way to help understand, interpret and communicate complex biological data. Principles of design, visual rhetoric/communication, and appropriate usage will be introduced. We will cover representation of different data types, concentrating on those generated by data-rich platforms such as next-generation sequencing applications, cytometry, and proteomics, and will discuss the use of visualization techniques applied to assessing data quality and troubleshooting. Various topics including dimension reduction, hierarchical visualizations, unsupervised learning, graph theory, networks/layouts and interactivity will be covered. We will review the algorithmic underpinnings of various methods that lead to their appropriate and effective use. Finally, we will review a variety of genomics/bioinformatics-related visualization tools that are available online, and will explore the use of lower-level approaches (like Matlab or R) to create beautiful and effective visualizations.

CRN: 62037
Subj: INFO
Num: 662
Title: Biomed Appl Nat Lang Processng  
Level: Graduate Non-Degree Graduate
Min CR: 3
Schedule Type: Lecture
Status: Active
Instructor: John D Osborne (P)


Prerequisites
Graduate level INFO 603 Minimum Grade of C

Description
Students will be introduced to Natural Language Processing (NLP) including core linguistic tasks such as tokenization, lemmatization/stemming, Part of Speech tagging, parsing and chunking. Applications covered include Named Entity Recognition, semantic role labeling, word sense disambiguation, normalization, information retrieval, question answering and text classification. Applications and data will have a biomedical focus, but no biology or medical background is required.

CRN: 62070
Subj: INFO
Num: 673
Title: Clinical Informatics JC  
Level: Graduate Non-Degree Graduate
Min CR: 1
Schedule Type: Lecture
Status: Active
Instructor: James J Cimino (P)


Prerequisites
Graduate level INFO 603 Minimum Grade of C

Description
Students will learn how to read, present, and critique primary research publications in clinical informatics. Journal club participants will present high-impact recent journal publications selected by course instructors and learn how to read the paper, write critiques, and organize analysis insights into review papers. Students must show evidence of prior preparation prior to journal clubs and write critiques to show comprehension of the topics throughout the semester.


CRN: 62055
Subj: INFO
Num: 691
Title: Bioinformatics Seminar I
Level: Graduate Non-Degree Graduate
Min CR: 1
Schedule Type: Lecture
Status: Active
Instructor: TBA


Prerequisites
Graduate level INFO 603 Minimum Grade of C

Description
For master’s student only. Students will learn how to prepare, present, and critique research presentations in bioinformatics by attending seminar presentations made by presenters. Seminars are presented by graduate students, faculty, visitors, or online speakers. Students must show evidence of prior preparation, active participation, and documented comprehension of the topics.

CRN: 62025
Subj: INFO
Num: 701
Title: Introduction to Bioinformatics 
Level: Graduate
Min CR: 3
Schedule Type: Lecture
Status: Active
Instructor: Zechen Chong (P)


Prerequisites
Graduate level INFO 603 Minimum Grade of C

Description
Introduction to bioinformatics and computational biology, with emphasis on concepts and application of informatics tools to molecular biology. It covers biological sequence analysis, gene prediction, genome annotation, gene expression analysis, protein structure prediction, evolutionary biology and comparative genomics, bioinformatics databases, cloud computing, basic R-based data analysis, simple programming skills using Perl, Linux/Unix environment and command lines, visual analytics, and social/legal aspects of open science. It will have a class research project component.


CRN: 62061
Subj: INFO
Num: 712
Title: Visual Analytics Biomed Resrch 
Level: Graduate
Min CR: 3
Schedule Type: Lecture
Status: Active
Instructor: Alexander Rosenberg (P)


Prerequisites
Graduate level INFO 603 Minimum Grade of C

Description
In this course, we will explore the use of visualization techniques as a concise and effective way to help understand, interpret and communicate complex biological data. Principles of design, visual rhetoric/communication, and appropriate usage will be introduced. We will cover representation of different data types, concentrating on those generated by data-rich platforms such as next-generation sequencing applications, cytometry, and proteomics, and will discuss the use of visualization techniques applied to assessing data quality and troubleshooting. Various topics including dimension reduction, hierarchical visualizations, unsupervised learning, graph theory, networks/layouts and interactivity will be covered. We will review the algorithmic underpinnings of various methods that lead to their appropriate and effective use. Finally, we will review a variety of genomics/bioinformatics-related visualization tools that are available online, and will explore the use of lower-level approaches (like Matlab or R) to create beautiful and effective visualizations.


CRN: 62056
Subj: INFO
Num: 762
Title: Biomed Appl Nat Lang Processng
Level: Graduate
Min CR: 3
Schedule Type: Lecture
Status: Active
Instructor: John D Osborne (P)


Prerequisites
Graduate level INFO 603 Minimum Grade of C

Description
Students will be introduced to Natural Language Processing (NLP) including core linguistic tasks such as tokenization, lemmatization/stemming, Part of Speech tagging, parsing and chunking. Applications covered include Named Entity Recognition, semantic role labeling, word sense disambiguation, normalization, information retrieval, question answering and text classification. Applications and data will have a biomedical focus, but no biology or medical background is required.

CRN: 62059
Subj: INFO
Num: 791
Title: Bioinformatics Seminar I
Level: Graduate
Min CR: 3
Schedule Type: Lecture
Status: Active
Instructor: TBA


Prerequisites
Graduate level INFO 603 Minimum Grade of C

Description
For doctoral student only. Students will learn how to prepare, present, and critique research presentations in bioinformatics by attending seminar presentations made by presenters. Seminars are presented by graduate students, faculty, visitors, or online speakers. Students must show evidence of prior preparation, active participation, and documented comprehension of the topics.