Melanie Colón Posted July 6, 2017 Share Posted July 6, 2017 INTRODUCTION TO PYTHON FOR BIOLOGISTShttp://www.prinformatics.com/course/introduction-to-python-for-biologists-ipyb04/This course is being delivered by Dr Martin Jones, an expert in Python andauthor of two text books,Python for Biologists [http://www.amazon.com/Python-Biologists-complete-programming-beginners/dp/1492346136/]Advanced Python for Biologists [http://www.amazon.com/Advanced-Python-Biologists-Martin-Jones/dp/1495244377/].Prices start at £475 and accommodation packages can be added for anadditional £260, includes all meals and accommodation on site for the week,arrival Sunday before the course starts)Course overview: Python is a dynamic, readable language that is a popularplatform for all types of bioinformatics work, from simple one-off scriptsto large, complex software projects. This workshop is aimed at completebeginners and assumes no prior programming experience. It gives an overviewof the language with an emphasis on practical problem-solving, usingexamples and exercises drawn from various aspects of bioinformatics work.After completing the workshop, students should be in a position to (1)apply the skills they have learned to tackle problems in their own researchand (2) continue their Python education in a self-directed way.Intended audience:This workshop is aimed at all researchers and technical workers with abackground in biology who want to learn programming. The syllabus has beenplanned with complete beginners in mind; people with previous programmingexperience are welcome to attend as a refresher but may find the pace a bitslow.Teaching format:The workshop is delivered over ten half-day sessions (see the detailedcurriculum below). Each session consists of roughly a one hour lecturefollowed by two hours of practical exercises, with breaks at theorganizer’s discretion. There will also be plenty of time for students todiscuss their own problems and data.Assumed background:Students should have enough biological background to appreciate theexamples and exercise problems (i.e. they should know about DNA and proteinsequences, what translation is, and what introns and exons are). Noprevious programming experience or computer skills (beyond the ability touse a text editor) are necessary, but you'll need to have a laptop withPython installed.Curriculum:Monday 27thModule 1: Introduction.We will start with a general introduction to Python and explain why it isuseful and how learning to program can benefit your research. Some timewill be taken to explain the format of the course. We will outline the edit-run-fix cycle of software development and talk about how to avoid commontext editing errors. In this session, we also check that the computinginfrastructure for the rest of the course is in place. Core conceptsintroduced: source code; text editors; whitespace; syntax and syntax error;and Python versions.Module 2: Output and text manipulation.This session will show students how to write very simple programs thatproduce output to the terminal and in doing so become comfortable withediting and running Python code. This session also introduces many of thetechnical terms that we’ll rely on in future sessions. We will run throughsome examples of tools for working with text and show how they work in thecontext of biological sequence manipulation. We also cover different typesof errors and error messages and learn how to go about fixing themmethodically. Core concepts introduced: terminals; standard output;variables and naming; strings and characters; special characters; outputformatting; statements; functions; methods; arguments; comments.Tuesday 28thModule 3: File IO and user interfaces.We will discuss about the importance of files in bioinformatics pipelinesand workflows during this session, and we then explore the Pythoninterfaces for reading from and writing to files. This involves introducingthe idea of types and objects and a bit of discussion about how Pythoninteracts with the operating system. The practical session is spentcombining the techniques from session 2 with the file IO tools to createbasic file-processing scripts. Core concepts introduced: objects andclasses; paths and folders; relationships between variables and values;text and binary files; newlines.Module 4: Flow control 1: loops.A discussion of the limitations of the techniques learned in session 3quickly reveals that flow control is required to write more sophisticatedfile-processing programs, at this point we will progress on to the conceptof loops. We look at the way in which Python loops work, and how they canbe used in a variety of contexts. We explore the use of loops and liststogether to tackle some more difficult problems. Core concepts introduced:lists and arrays; blocks and indentation; variable scoping; iteration andthe iteration interface; ranges.Wednesday 29thModule 5: Flow control 2: conditionals.We will use the idea of decision-making in session 5 as a way to introduceconditional tests and outline the different building-blocks of conditionsbefore showing how conditions can be combined in an expressive way. We lookat the different ways that we can use conditions to control program flow,and how we can structure conditions to keep programs readable. Coreconcepts introduced: Truth and falsehood; Boolean logic; identity andequality; evaluation of statements; branching.Module 6: Organizing and structuring code.In session 6 we will discuss functions that we would like to see in Pythonbefore considering how we can add to our computational toolbox by creatingour own. We examine the nuts and bolts of writing functions before lookingat best-practice ways of making them usable. We also look at a couple ofadvanced features of Python – named arguments and defaults. Core conceptsintroduced: argument passing; encapsulation; data flow through a program.Thursday 30thModule 7: Regular expressions.A range of common problems in bioinformatics can be described in terms ofpattern matching; we will discuss these and give an overview of Python’sregex tools. We look at the building blocks of regular expressionsthemselves, and learn how they are a general solution to the problem ofdescribing patterns in strings, before practising writing some specificexamples of regular expressions. Core concepts introduced: domain-specificlanguages; sessions and namespaces.Module 8: Dictionaries.We discuss a few examples of key-value data and see how the problem ofstoring them is a common one across bioinformatics and programming ingeneral. We learn about the syntax for dictionary creation and manipulationbefore talking about the situations in which dictionaries are a better fitthat the data structures we have learned about thus far. Core conceptsintroduced: paired data types; hashing; key uniqueness; argument unpackingand tuples.Friday 1stModule 9: Interaction with the file system.In the final session e discuss the role of Python in the context of abioinformatics workflow, and how it is often used as a language to “glue”various other components together. We then look at the Python tools forcarrying out file and directory manipulation, and for running externalprograms – two tasks that are often necessary in order to integrate our ownprograms with existing ones. Core concepts introduced: processes and sub-processes; the shell and shell utilities; program return values.Please email any inquiries to firstname.lastname@example.org or visit ourwebsite www.prinformatics.comPlease feel free to distribute this material anywhere you feel is suitable-----------------------------------------------------------------------------------------------------------------PR informatics other courses1. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS #BIGB3rd – 7th July 2017, Scotland, Dr. Nic Blouin, Dr. Ian Misnerhttp://www.prinformatics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/2. 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TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 #TSMEDr. Andrew Parnell - Date and location to be confirmed-------------------------------------------------------------------------------------------------------------------Oliver Hooker PhD.PR informatics2017 publications -Ecosystem size predicts eco-morphological variability in post-glacialdiversification. Ecology and Evolution. In press.The physiological costs of prey switching reinforce foragingspecialization. Journal of animal ecology.prinformatics.comtwitter.com/PRinformaticsfacebook.com/prstatistics/prstatistics.com/organiser/oliver-hooker/3/1, 128 Brunswick StreetGlasgowG1 1TF+44 (0) 7966500340 Link to comment Share on other sites More sharing options...
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