About this course
An introduction to knowledge integration and statistical strategies utilized in fashionable Techniques Biology, Bioinformatics, and Techniques Pharmacology analysis. The course covers strategies of processing uncooked knowledge from genome-wide mRNA expression research (microarrays and RNA-seq) together with knowledge normalization, differential expression, clustering, enrichment evaluation and construct networks. The course contains hands-on directions for utilizing the instruments and establishing pipelines, but it surely additionally covers the maths behind the strategies utilized within the instruments. The course is usually appropriate for newbie graduates and superior college college students in majors comparable to biology, arithmetic, physics, chemistry, pc science, biomedical and electrical engineering. The course might be helpful to researchers encountering massive knowledge units in their very own analysis. The course presents software program instruments developed by Ma’ayan Laboratories (http://labs.icahn.mssm.edu/maayanlab/) from the Icahn Faculty of Drugs at Mount Sinai, in addition to visualization instruments and different freely obtainable knowledge evaluation. The final word purpose of the course is to allow contributors to make use of the strategies offered on this course to research their very own knowledge for their very own tasks. For contributors not working within the area, the course introduces present analysis challenges confronted within the area of computational techniques biology.
Versatile deadlines Versatile deadlines Reset deadlines to suit your schedule.Shareable Certificates Shareable Certificates Examine for a certificates 100% full 100% on-line Get began now immediately and be taught by yourself schedule.Lock 3/6 inTechniques Biology and Majors in Biotechnology Fast Degree Fast Degree Hours AccomplishedAbout 30 hours to finishOut there languagesSubtitles: French, Portuguese (Europe), Russian, English, Spanish
Syllabus – What you’ll be taught from this course
Weekfirst
Week 1
Course Overview and Introduction
The ‘Introduction to Advanced Techniques’ module discusses advanced techniques and results in the concept a cell will be considered a fancy system or a fancy agent dwelling in an atmosphere as sophisticated as we’re. The module ‘Introduction to Biology for Engineers’ offers an introduction to among the central subjects in mobile and molecular biology for many who don’t but have a background within the area. This isn’t a complete protection of cell and molecular biology. The purpose is to supply an entry level to spur these within the area, coming from different disciplines, to begin learning biology.
Week2
Week 2
Community evolution mannequin and topology
Within the module ‘Modeling Topology and Networks Evolution’, we offer a number of lectures on the historic perspective of community evaluation in techniques biology. The main target is on in-silico community improvement fashions. These are easy computational fashions that, based mostly on a number of guidelines, can generate topological networks just like these noticed in organic techniques.
Week3
Week 3
Sorts of organic networks
The module ‘Sorts of Organic Networks’ talks concerning the several types of networks generally constructed and analyzed in techniques biology and techniques pharmacology. This lecture concludes with the concept of useful interconnection networks (FANs). This lecture is adopted by lectures discussing find out how to generate FANs and find out how to use these networks to research gene lists.
Week4
Week 4
Information processing and identification of differentially expressed genes
This lecture set within the ‘Information Processing and Identification of differentially expressed genes’ module discusses knowledge normalization strategies first, adopted by quite a lot of lectures dedicated to explaining the issue of identification. differentially expressed genes with a give attention to understanding the interior workings of a brand new technique developed by Ma’ayan Laboratories referred to as Attribute Route.
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Week5
Week 5
Genome Enrichment and Community Evaluation
Within the ‘Gene Set Enrichment and Community Evaluation’ module, the main target is on the instruments developed by Ma’ayan Laboratories for genomic aggregation evaluation. Among the instruments that might be mentioned embrace: Enrichr, GEO2Enrichr, Expression2Kinases and DrugPairSeeker. As well as, one lecture might be dedicated to the tactic we name enrichment vector clustering that we now have developed, and two lectures will describe the favored genomic subset enrichment evaluation (GSEA) technique and an improved technique we now have developed referred to as principal angle enrichment evaluation (PAEA).
Week6
Week 6
Deep sequence knowledge processing and evaluation
The set of lectures within the ‘Deep Sequencing Information Processing and Evaluation’ module will cowl the essential steps and customary paths for analyzing RNA-seq and ChIP-seq knowledge away from uncooked knowledge to gene lists to metrics. These lectures additionally cowl UNIX/Linux instructions and a few programming parts of R, a well-liked free statistical software program. Observe that since these lectures have been developed and recorded within the Fall of 2013, there could also be higher instruments in use now as the sphere is quickly evolving.
Week7
Week 7
Principal Part Evaluation, Self-Organizing Map, Community Based mostly Grouping, and Hierarchical Clustering
This module is dedicated to totally different clustering strategies: principal part evaluation, self-organizing maps, network-based clustering and hierarchical clustering. The speculation behind these analytical strategies is detailed and adopted by some sensible demonstrations of the strategies for functions utilizing R and MATLAB.
Week8
Week 8
Sources for knowledge integration
The lectures within the ‘Sources for Information Integration’ module are concerning the several types of networks generally constructed and analyzed in techniques biology and techniques pharmacology. These lectures start with the concept of useful interconnection networks (FANs). This lecture is adopted by a number of lectures discussing find out how to generate FANs from totally different sources and find out how to use these networks to research gene lists and construct a puzzle that can be utilized to attach knowledge. genome knowledge with phenotypic knowledge.
Week9
Week 9
Crowdsourcing: Microtasks and Megatasks
The ultimate set of lectures presents the concept of neighborhood sourcing. MOOCs provide the chance to work collectively on tasks which might be troublesome to finish alone (microtasks) or compete to implement the most effective algorithms to unravel troublesome issues (megatasks). You should have the chance to take part in numerous neighborhood sourcing tasks: microtasks and megatasks. These tasks are particularly designed for this course.
Weekten
Week 10
Remaining examination
The ultimate examination contains a number of alternative questions from subjects lined by all modules of the course. Some questions could ask you to carry out among the analytical strategies you discovered throughout the course on new datasets.
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