"A look at the methods and algorithms used to predict protein structure A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structu ..."
"Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for ..."
"Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for ..."
"J. Wang, H. Lee, and S. Ahmad. Prediction and evolutionary information analysis
of protein solvent accessibility using multiple linear regression. Proteins, 61:481–
491, 2005. 208. Z. Xu, C. Zhang, S. Liu, and Y. Zhou. QBES: Predicting real
values of solvent accessibility from sequences by efficient, constrained energy
optimization. Proteins, 63:961–966, 2006. 209. H. Naderi-Manesh, M. Sadeghi, S
. Arab, and A.A.M. Movahedi. Predict ..."
"Learning analytics (or educational big data) tools are increasingly being deployed on campuses to improve student performance, retention and completion, especially when those metrics are tied to funding. Providing personalized, real-time, actionable feedback through mining and analysis of large data sets, learning analytics can illuminate trends and predict future outcomes. While promising, there is limited and mixed empirical evidence ..."
"Current Innovations, Future Potential, and Practical Applications Jaime Lester,
Carrie Klein, Aditya Johri, Huzefa Rangwala. Aditya Johri is an Associate
Professor in the Information Sciences and Technology Department at George
Mason ..."
"ASHE Higher Education Report Lester, Carrie Klein, Huzefa Rangwala, Aditya
Johri. University of ... Retrieved fromhttps://wcer.wisc.edu/docs/working-papers/
Working_Paper_No_2014_03.pdf Hora, M. T., & Holden, J. (2013). Exploring the
role of ... Journal of Computing in Higher Education, 25, 68–92. Hughes, J. ...
Retrieve from http://publications.cetis.ac.uk/2012/500 Kezar, A. (2001). ...
Rethinking the “L” word in higher education: ..."
"This SpringerBrief covers the technical material related to large scale hierarchical classification (LSHC). HC is an important machine learning problem that has been researched and explored extensively in the past few years. In this book, the authors provide a comprehensive overview of various state-of-the-art existing methods and algorithms that were developed to solve the HC problem in large scale domains. Several challenges faced by ..."
"Primary Structure Amino acids form the basic building blocks of proteins. Amino
acids consists of a central carbon atom (Cα) attached by an amino (NH2), a
carboxyl (COOH) group, and a side chain (R) group. The side chain group ..."
"Babbar, R., Partalas, I., Gaussier, E., Amini, M.R.: On flat versus hierarchical
classification in large-scale taxonomies. In: Advances in Neural Information
Processing Systems, pp. 1824– 1832 (2013) 3. Babbar, R., Partalas, I., Gaussier,
E., Amini ..."
"In this book, the authors provide a comprehensive overview of various state-of-the-art existing methods and algorithms that were developed to solve the HC problem in large scale domains."