An Online Bioinformatics Curriculum

Online learning initiatives over the past decade have become increasingly comprehensive in their selection of courses and sophisticated in their presentation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university education on the internet, free of charge, a real possibility. At this pivotal moment it is appropriate to explore the potential for obtaining comprehensive bioinformatics training with currently existing free video resources. This article presents such a bioinformatics curriculum in the form of a virtual course catalog, together with editorial commentary, and an assessment of strengths, weaknesses, and likely future directions for open online learning in this field.

[1]  Gerald J. Sussman,et al.  Structure and Interpretation of Computer Programs, Second Edition , 1996 .

[2]  T. Hughes,et al.  Signals and systems , 2006, Genome Biology.

[3]  Guy M. McKhann,et al.  Biochemistry. 3rd edition , 1988, The Yale Journal of Biology and Medicine.

[4]  Alfred Bork,et al.  Multimedia in Learning , 2001 .

[5]  Robert M. Gray,et al.  Probability, Random Processes, And Ergodic Properties , 1987 .

[6]  Peter Szolovits,et al.  What Is a Knowledge Representation? , 1993, AI Mag..

[7]  Gerald J. Sussman,et al.  Structure and interpretation of computer programs , 1985, Proceedings of the IEEE.

[8]  Errol C. Caby.  An Introduction to Statistical Signal Processing , 2006, Technometrics.

[9]  Xin-She Yang,et al.  Introduction to Algorithms , 2021, Nature-Inspired Optimization Algorithms.

[10]  Duc T. Nguyen,et al.  Numerical Methods with Applications , 2011 .

[11]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.

[12]  Neil C. Rowe.  Artificial intelligence through Prolog , 1988 .

[13]  Edward A. Bender,et al.  A Short Course in Discrete Mathematics , 2004 .

[14]  Charles M. Grinstead,et al.  Introduction to probability , 1999, Statistics for the Behavioural Sciences.

[15]  Kathy Sierra,et al.  Head first Java - your brain on Java: a learner's guide , 2003 .

[16]  Ronald L. Rivest,et al.  Introduction to Algorithms, 3rd Edition , 2009 .

[17]  Wim P. Krijnen,et al.  Applied Statistics for Bioinformatics using R , 2009 .

[18]  Eric R. Ziegel,et al.  Statistical Methods in Bioinformatics , 2002, Technometrics.

[19]  V. Parmon,et al.  Entropy and Information , 2009 .

[20]  E. Bender,et al.  Foundations of combinatorics with applications , 1991 .

[21]  David B. Searls,et al.  Ten Simple Rules for Online Learning , 2012, PLoS Comput. Biol..

[22]  K. K. Nambiar,et al.  Foundations of Computer Science , 2001, Lecture Notes in Computer Science.

[23]  Gilbert Strang,et al.  Computational Science and Engineering , 2007 .

[24]  Mehmed Kantardzic,et al.  Learning from Data , 2011 .

[25]  Ewan Klein,et al.  Natural Language Processing with Python , 2009 .

[26]  Barbara Means,et al.  Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies , 2009 .

[27]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[28]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[29]  Rappold,et al.  Human Molecular Genetics , 1996, Nature Medicine.

[30]  Dan Gusfield,et al.  Algorithms on Strings, Trees, and Sequences - Computer Science and Computational Biology , 1997 .

[31]  Chris Arney,et al.  Networks, Crowds, and Markets: Reasoning about a Highly Connected World (Easley, D. and Kleinberg, J.; 2010) [Book Review] , 2013, IEEE Technology and Society Magazine.

[32]  Philippe Flajolet,et al.  Analytic Combinatorics , 2009 .

[33]  E. David,et al.  Networks, Crowds, and Markets: Reasoning about a Highly Connected World , 2010 .

[34]  Eitan M. Gurari,et al.  Introduction to the theory of computation , 1989 .

[35]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[36]  V. Lakshmi Narayanan,et al.  Top-down Calculus , 1989 .

[37]  Bart Funnekotter.  Cambridge Cambridge University , 2005 .

[38]  Riccardo Poli,et al.  A Field Guide to Genetic Programming , 2008 .

[39]  Ashutosh Kumar Singh,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2010 .

[40]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[41]  Arthur B. Markman,et al.  Knowledge Representation , 1998 .

[42]  John N. Tsitsiklis,et al.  Introduction to Probability , 2002 .

[43]  Lee D. Davisson,et al.  An Introduction To Statistical Signal Processing , 2004 .

[44]  Larry Wasserman,et al.  All of Statistics , 2004 .