Biodiversity/Ecological Informatics

Analyze genomic sequences through understanding and using a variety of bioinformatics algorithms and software tools.  Interdisciplinary approach integrating informatics, statistics, and biology.  Graduate-level requirements include leading a discussion on a current paper or give a tutorial on a bioinformatics tool as part of the Major Concept Exercises category.

This course will introduce the fundamental concepts of geographic information systems technology (GIST).  It will emphasize equally GISystems and GIScience.  Geographic information systems are a powerful set of tools for storing and retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes.  In contrast, geographic information science is concerned with both the research on GIS and with GIS.    As Longley et.al., notes (2001, vii) ¿GIS is fundamentally an applications-led technology, yet science underpins successful applications.¿  This

Organizing information in electronic formats requires standard machine-readable languages. This course covers recent standards including XML (eXtensible Markup Language) and related technologies (XPath and XSLT) which are used widely in current information organization systems. Building on a sounding understanding of XML technologies, the course also introduces students to newer standards that support the development of the Semantic Web.

Neural networks are a branch of machine learning that combines a large number of simple computational units to allow computers to learn from and generalize over complex patterns in data. Students in this course will learn how to train and optimize feed forward, convolutional, and recurrent neural networks for tasks such as text classification, image recognition, and game playing.

Students will learn from experts from projects that have developed widely adopted foundational Cyber infrastructure resources, followed by hands-on laboratory exercises focused around those resources. Students will use these resources and gain practical experience from laboratory exercises for a final project using a data set and meeting requirements provided by domain scientists. Students will be provided access to computer resources at: UA campus clusters, iPlant Collaborative and at NSF XSEDE.

Introduction to the theories and practices used in the organization of information. Overview of national and international standards and practices for access to information in collections.