Whats a good book/website/tutorial to start learning Python?
Seqanswers Leaderboard Ad
Collapse
Announcement
Collapse
No announcement yet.
X
-
Originally posted by thinkRNA View PostWhats a good book/website/tutorial to start learning Python?
There's a new Python book for Bioinformatics from O'Reilly. No idea what the quality is like.
Comment
-
Originally posted by Calico View PostHello everybody,
My rather limited bioinfromatics skills come from having done some microarray data analysis in R (following a template code) and some minor coursework. So, I consider myself quite a newbie to the subject. I will quite soon be shaking hands with some sequencing data (from a Helicos machine) and need to prepare myself for this.
Being of a younger generation, I would say I can handle computers pretty well. So far I have, as recommended in this nice thread, started to take a look at the Unix and Perl for Biologist tutorial and installed Ubuntu in Virtual PC on my Windows computer.
What I'd like to ask you, SEQanswers community, is whether you can suggest me anything helpful. Am I starting out in the right way? I will get some bioinformatics help along the way, though I am unsure to what extent. Also, I see this as a part of my future career, so I am not just doing this for one particular project.
Edit: I have just realized that the Helicos software package uses Python.
Comment
-
Originally posted by quinlana View PostOne more vote for Python. I spent my grad career developing in Perl and C++. For some reason, I always wrote Perl code as "one-off" scripts. Moreover, the syntax and code structure made it difficult for me to make sense of even my most well-documented Perl scripts.
On the other hand, from the moment I began using Python, I started developing more in the style I do when writing C++ tools: that is, with an emphasis on code "reusability" and clarity. For some reason, Python just "feels" good and lends itself to clean, simple and reusable code. The best part is that its approach to object orientation is rather well done and allows one to think the same way as when writing Java or C++ code.
Therefore, I think learning Python first with a concerted effort towards learning objects, iterators, inheritance and developing modules, would be best. It will make a transition to Java or C++ much easier.
Comment
-
Originally posted by Calico View PostHello everybody,
My rather limited bioinfromatics skills come from having done some microarray data analysis in R (following a template code) and some minor coursework. So, I consider myself quite a newbie to the subject. I will quite soon be shaking hands with some sequencing data (from a Helicos machine) and need to prepare myself for this.
Being of a younger generation, I would say I can handle computers pretty well. So far I have, as recommended in this nice thread, started to take a look at the Unix and Perl for Biologist tutorial and installed Ubuntu in Virtual PC on my Windows computer.
What I'd like to ask you, SEQanswers community, is whether you can suggest me anything helpful. Am I starting out in the right way? I will get some bioinformatics help along the way, though I am unsure to what extent. Also, I see this as a part of my future career, so I am not just doing this for one particular project.
Edit: I have just realized that the Helicos software package uses Python.
Comment
-
Originally posted by JohnK View PostI wrote a longer response, but for some reason it never posted or maybe it posted to the wrong forum. Java and c++ are object oriented, which means everything you do will be within the confines of classes, objects, encapsulation and abstraction. For simple programs, you might want to leave simple flat/text file manipulation to a scripting language; ie leave the scripting tasks to scripting languages like perl, shell, and oop oriented tasks to the oop oriented programming languages. I think for bioinformatics purposes, a scripting language like perl, python, etc will suffice. Perl seems to be by far the most popular and there are large libraries like CPAN and BioPerl to support your coding. Perl is also very fast, but not as fast as shell programming. Learning shell programming in a Unix/Linux environment is a priceless skill and will save you much time. All the statisticians I've met have and are using 'R'. I myself haven't learned R, but it's definitely a future endeavor. Hope that helps.
Comment
-
Originally posted by JohnK View PostAw man! I love perl, but scripting languages are all the same to me. Just remember to hit '#' constantly.Sameet Mehta (Ph.D.),
Visiting Fellow,
National Cancer Insitute,
Bethesda,
US.
Comment
-
I've come to rely more and more on awk. Being a self-trained perl programmer I find it fascinating to see how much I can do with (nearly) oneliners in awk instead of writing multiple-line perl scripts. Many of my input/output files are tab separated, which is ideal for awk.
Next on my list is learning python...
Comment
-
Originally posted by damiankao View PostI got to go with Python too. Perl has great available libraries, but Python is just so much more agile than Perl. Just having the dot notation format and slice syntax makes things so much easier.
As for CML, awk is awesome, but can lack some syntax sugar, in my opinion. A lot of the stuff I do on the CML in perl is just a manipulation along the lines of:
< <in_file> perl -e 'while(<>){ #splitting, pushing onto an array, printing out, and then piping to some text filters, etc...# }' | a filter > <out file> &
I wouldn't use perl to do things that filters and sed/awk can do for you, but knowing unix/linux filter and shell commands is a priceless skill that saves incredible amounts of time. I think I can say that without someone yelling at me.
Comment
-
Originally posted by flxlex View PostI've come to rely more and more on awk. Being a self-trained perl programmer I find it fascinating to see how much I can do with (nearly) oneliners in awk instead of writing multiple-line perl scripts. Many of my input/output files are tab separated, which is ideal for awk.
Next on my list is learning python...Sameet Mehta (Ph.D.),
Visiting Fellow,
National Cancer Insitute,
Bethesda,
US.
Comment
-
Originally posted by ymc View PostDoes Python has a free bioinformatics library like BioPerl? I find that BioPython is quite lacking for now. I am wondering if there are better alternatives.
You can already do a lot with it: see this thread, in which I've advertised it, and, of course, the HTSeq web page.
Simon
Comment
-
Originally posted by quinlana View PostI learned the basics from python.org and used O'Reilly's "Python Cookbook" to get a feel for the subtleties and advanced usage. In my case, however, I was mainly just needed to know the syntax and basic data structures as I already knew how to program.
There's a new Python book for Bioinformatics from O'Reilly. No idea what the quality is like.
http://oreilly.com/catalog/9780596154516/
Comment
Latest Articles
Collapse
-
by seqadmin
The field of immunogenetics explores how genetic variations influence immune responses and susceptibility to disease. In a recent SEQanswers webinar, Oscar Rodriguez, Ph.D., Postdoctoral Researcher at the University of Louisville, and Ruben MartÃnez Barricarte, Ph.D., Assistant Professor of Medicine at Vanderbilt University, shared recent advancements in immunogenetics. This article discusses their research on genetic variation in antibody loci, antibody production processes,...-
Channel: Articles
Yesterday, 07:24 PM -
-
by seqadmin
Next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR) are essential techniques for investigating the genome, transcriptome, and epigenome. In many cases, choosing the appropriate technique is straightforward, but in others, it can be more challenging to determine the most effective option. A simple distinction is that smaller, more focused projects are typically better suited for qPCR, while larger, more complex datasets benefit from NGS. However,...-
Channel: Articles
10-18-2024, 07:11 AM -
ad_right_rmr
Collapse
News
Collapse
Topics | Statistics | Last Post | ||
---|---|---|---|---|
Started by seqadmin, 11-01-2024, 06:09 AM
|
0 responses
27 views
0 likes
|
Last Post
by seqadmin
11-01-2024, 06:09 AM
|
||
New Model Aims to Explain Polygenic Diseases by Connecting Genomic Mutations and Regulatory Networks
by seqadmin
Started by seqadmin, 10-30-2024, 05:31 AM
|
0 responses
21 views
0 likes
|
Last Post
by seqadmin
10-30-2024, 05:31 AM
|
||
Started by seqadmin, 10-24-2024, 06:58 AM
|
0 responses
25 views
0 likes
|
Last Post
by seqadmin
10-24-2024, 06:58 AM
|
||
New AI Model Designs Synthetic DNA Switches for Targeted Gene Expression in Specific Cell Types
by seqadmin
Started by seqadmin, 10-23-2024, 08:43 AM
|
0 responses
57 views
0 likes
|
Last Post
by seqadmin
10-23-2024, 08:43 AM
|
Comment