Introduction to Bioinformatics

Date

2013-01-01

Author

Can, Tolga

Metadata

Show full item record

Item Usage Stats

189
views

0
downloads

URI

http://link.springer.com/book/10.1007/978-1-62703-748-8
https://hdl.handle.net/11511/83325

Relation

miRNomics MicroRNA Biology and Computational Analysis

Collections

Department of Computer Engineering, Book / Book chapter

Suggestions

OpenMETU
Core

Introduction to Bioinformatics Can, Tolga(2009) This course covers computational techniques for mining the large amount of information produced by recent advances in biology, such as genome sequencing and microarrray technologies. Main topics of the course include: DNA and protein sequence alignment, sequence motifs/patterns, phylogenetic trees, protein structures: prediction, alignment, classification microarray data analysis: normalization, clustering and biological networks.
Introduction to Electrical Circuit Analysis Ergül, Özgür Salih (John Wiley & Sons, West Sussex, UK, 2017-01-01)
Introduction to Computer Assisted Language Learning Tools Seferoğlu, Gölge(2010) This course introduces pre-service teachers of English to Computer-Assisted Language Learning (CALL) tools. In addition to giving an overview of the uses of CALL tools in teaching/learning, the course will cover a review of interactive instructional technologies in language teaching/learning, the Internet in English language teaching, and evaluation of English language teaching software and use of Web 2.0 tools in the language classroom. Implications of CALL in language classrooms will also be discussed. St...
Introduction to Real Analysis (Math 349) Ozan, Yıldıray(2020-10-13) Course Content LUB Property of real numbers. Compactness, connectedness, limits and continuity in metric spaces. Sequences and series of scalars, complete metric spaces, limsup. Sequences and series of functions, uniform convergence, applications.
Introduction to the Special Issue on Fuzzy Analytics and Stochastic Methods in Neurosciences Kropat, E.; Turkay, M.; Weber, Gerhard Wilhelm (Institute of Electrical and Electronics Engineers (IEEE), 2020-01-01) The papers in this special section examine the use of fuzzy analytics and stochastic methods in the field of neuroscience. Recent theoretical and technological advancements provide new and deeper insights into the fundamental mechanisms of information processing in the neural system. This important process is accompanied by the tremendous rise of experimental data, which are waiting for further exploration. Modern methodologies and tools from neuroimaging, brain imaging, optogenetic devices, and in vitro an...

Citation Formats

T. Can, Introduction to Bioinformatics. 2013.