Also known as Edit Distance, it is the number of transformations (deletions, insertions, or substitutions) required to transform a source string into the target one. For example, if the target term is “book” and the source is “back”, you will need to change the first “o” to “a” and the second “o” to “c”, which will give us a Levenshtein Distance of 2.Edit Distance is very easy to implement, and it is a popular challenge during code interviews

Additionally, some frameworks also support the Damerau-Levenshtein distance:

Damerau-Levenshtein distance

It is an extension to Levenshtein Distance, allowing one extra operation: Transposition of two adjacent characters:

Ex: TSAR to STAR

Damerau-Levenshtein distance = 1  (Switching S and T positions cost only one operation)

Levenshtein distance = 2  (Replace S by T and T by S)

• January 20th, 2016 - New! Bpipe 0.9.9 released!
• Download latest, all
• Documentation
• Mailing List (Google Group)

Bpipe has been published in Bioinformatics! If you use Bpipe, please cite:

Sadedin S, Pope B & Oshlack A, Bpipe: A Tool for Running and Managing Bioinformatics Pipelines, Bioinformatics

Address of the bookmark: http://docs.bpipe.org/

More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us

Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/

Perl's second wave of adoption came from the growth of the world wide web. Dynamic web pages—the precursor to modern web applications—were easy to create with Perl and CGI. Thanks to Perl's ubiquity as a language for system administrators and its power to manipulate text, it was the default choice for web programming. Its presence everywhere made it popular and, in some ways, the duct tape of the Internet.

Web Application Development

The old days of CGI programs and the simple development style that represented seem clunky. Web pages have become web applications. Development has moved from generating static HTML to both client and server side programming, with rich client interfaces and powerful backends.

Perl is still well suited for developing modern web apps. The language grows more powerful and easier to use every year, the available libraries are wonderful and keep getting better, and the inventions and discoveries available in modern Perl are unsurpassed.

In particular, a modern Perl developer can do amazing things with modern Perl tools. If you still think of Perl web development as a cgi-bin directory full of messy scripts that spew warnings to STDERR, you're a decade out of date. Better yet, you can replace that mess piecemeal, thanks to the new tools and techniques of modern Perl. See, for example, the ever-growing list of technologies Built in Perl.

Modern Perl Web Frameworks

While the old wave of web development may have made the CGI.pm module central, modern Perl web programming follows a stricter separation of business logic, URL and request routing, and output. The days of slinging a string here, an array there, a Perl hash yonder, declaring every variable at the top of the program, and maybe making a subroutine are gone. The Perl world has seen the value of abstraction and ways to mechanize away boilerplate. Perl has dozens of frameworks and toolkits designed to make web development and deployment simpler.

Any of a dozen of these frameworks will help you do great things, but three in particular stand out. You can build web sites and web applications of tremendous value with all three. These are neither the only good possibilities (think of POE or Jifty or Continuity or...) nor the only mechanisms for web programming with Perl (see Mechanize or LWP or Mojo::UserAgent for more). Yet if you want three good options to choose between, start here.

Catalyst

The Catalyst framework is a flexible and powerful system for building small to large web apps. It uses the Moose object system to provide great APIs for extension and further development. It's the most mature of the modern top Perl web frameworks, yet it retains its flexibility and vibrancy. In particular, its plugin and extension ecosystem allows it to evolve to provide new and essential features.

Catalyst has embraced the Plack/PSGI standard for Perl web deployment and recent versions are exploring high-scalability, event-based request handling models.

Dancer

The Dancer framework is deliberately minimal in syntax and scope, but it also has a vibrant plugin ecosystem. Dancer particularly excels for smaller sites and applications, though good programmers can build larger things with it.

The first version of Dancer was easy to use. Dancer 2 continues that ease while improving the internals and robustness of applications.

Mojolicious

The Mojolicious (Mojo) framework has a real-time design based on high performance event handling. Its focus is solving new and interesting problems in simple and effective ways, and the project has produced a lot of new code that does old things in better ways.

In particular, Mojolicious goes to great lengths to support new web standards, such as CSS 3, web sockets, and HTTP 2.

Where Catalyst embraces the CPAN fully, Mojolicious by design provides most of what an average app might need in a single download. It's still fully compatible with the CPAN, but the intention is to provide good working defaults in a package that's easy to start with. Mojo's fans are quick to praise it as fun to develop.

A modern Perl web developer should be familiar with at least one of these frameworks.

Modern Perl Storage Mechanisms

Perl's venerable DBI module has been the focal point of database access since its invention. Its design allows it to provide the same interface to huge relational databases and flat files alike through its DBD extension mechanism. Yet the DBI by itself isn't the be-all, end-all of data storage and access in Perl.

DBIx::Class

DBIx::Class sits on top of DBI to provide an API to your database based on the concept of queries and results. This is often sufficient to remove all but the most complicated of SQL from your code, leaving you to manipulate your business models instead of the small details of how a relational database works. The power and maintainability you receive is well the small cost of the learning curve.

Even better, DBIC can manage (and even generate) your database schema for you.

Recent versions of DBIC have demonstrated that a well-written ORM can perform much better than even clever hand-written code. Because it builds on the Perl DBI, it scales everywhere from SQLite to PostgreSQL, MySQL, Oracle, and more.

Rose::DB

The lesser-known but no less powerful Rose::DB::Object builds on Rose::DB to provide an object-relational mapper for Perl. While its high level features most directly compare to those of DBIx::Class, it's often measurably faster.

NoSQL on the CPAN

Of course the CPAN has modules for almost any NoSQL database or job queue or persistence mechanism you could name, and several you have never heard of. Everything you need is a quick CPAN or cpanm away!

Modern Perl Deployment Strategies

In the early days of the web, deploying a Perl web application meant putting one or more .cgi or .pl files in a special directory and hoping that your system administrator had everything configured correctly. The execution model was often slow and cumbersome, and accessing shared resources such as databases was often tricky.

Modern Perl has better choices. While deployment strategies are the source of many arguments, the return on your investment from learning the modern way is impressive.

Plack/PSGI

The PSGI specification (as exemplified by Plack) describes a strategy for building Perl web apps independent of server and with the possibility to share custom processing behaviors.

In other words, it's a standard for writing Perl apps to take advantage of the huge ecosystem of Perl development available on the CPAN without tying yourself to a server like Apache, Apache 2, nginx, or anything else.

Any good modern Perl web framework (including those listed here) supports PSGI. Several deployment mechanisms exist to meet various business needs which also support PSGI. In particular, you can deploy the same application with a local testing server on your own machine as you can to your production server or servers without changing your application at all.

mod_perl

The older but still viable mod_perl Apache httpd module embeds Perl into the web server. This was the first widespread persistence mechanism for Perl web applications themselves and it's still popular to this day, though PSGI compliance is often the choice for new development. (PSGI handlers to use mod_perl as the backend are available.)

Modern Perl developers should familiarize themselves with PSGI and the wealth of available Plack middleware.

Perl Web Development

Of course no discussion of Perl web development would be complete without mentioning the strength of the CPAN. Almost any project will benefit from the wealth of freely available libraries built to solve real problems. These distributions run the gamut from full-blown web frameworks and content management systems to APIs for web services, development tools, testing systems, and interfaces to document formats and external resources.

For example, if you need to write a web service which accepts JSON data and produces Excel spreadsheets, you can glue together a few CPAN distributions and get the job done early. If you need to consume XML from a remote service and emit a PDF, you're in luck.

Perl's prowess as a general purpose programming language as well as its flexibility and power in managing text and gluing systems together make it a wonderful fit for web development. The community's adoption of modern Perl standards such as PSGI and Plack only enhance your power.

Web application development in Perl is still viable, and modern Perl tools and techniques and libraries make it more powerful and pleasant than ever.

This readme covers all necessary instructions for the impatient to get andi up and running. For extensive instructions please consult the manual.

More at https://github.com/evolbioinf/andi/

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full

Essential Qualifications: Ph.D. (Bioinformatics/ Biophysics/ Biotechnology or any other stream of biological/ physical sciences) with a minimum of two publications in reputed peer reviewed journals in the area of structural bioinformatics or biophysics or biomolecular modeling/ simulation.

Job description: Development of bioinformatics tools and algorithms/software for structure based analysis of biomolecular systems. Programmatic access to major biomolecular databases using APIs Knowledge based prediction and analysis of biomolecular structure, function and interactions. Docking/simulations for inhibitor design.

Desirable Qualifications (Research Associate/s): i) Strong computer programming skills (in Python/PERL/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment).

ii) Extensive experience in computational analysis of biomolecular structure/interactions and usage of advanced biomolecular simulation softwares. iii) Adequate knowledge of major databases, webservers and softwares in the area of biomolecular structure/function and drug design. iv) Familiarity with Parallel Programming environments and experience in usage of high-end HPC clusters.

The candidates must highlight their experience in above mentioned fields/topics in their CV. Initial appointment will be for a period of 1 year, subject to extension after review of performance.

Emoluments: As per DST, GOI norms and commensurate with experience.

More at https://www.iisc.ac.in/positions-open/

More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leidosbiomed&id=2040

Upgrading to R 3.2.0 on Windows

If you are using Windows you can easily upgrade to the latest version of R using the installr package. Simply run the following code:

# installing/loading the latest installr package:
install.packages("installr"); library(installr) #load / install+load installr
 
updateR() # updating R.

Running “updateR()” will detect if there is a new R version available, and if so it will download+install it (etc.).

If you are an R blogger yourself you are invited to add your own R content feed to this site (Non-English R bloggers should add themselves- here)

NEW FEATURES

• anyNA() gains a recursive argument.
• When x is missing and names is not false (including the default value), Sys.getenv(x, names) returns an object of class "Dlist" and hence prints tidily.
• (Windows.) shell() no longer consults the environment variable SHELL: too many systems have been encountered where it was set incorrectly (usually to a path where software was compiled, not where it was installed). R_SHELL, the preferred way to select a non-default shell, can be used instead.
• Some unusual arguments to embedFonts() can now be specified as character vectors, and the defaults have been changed accordingly.
• Functions in the Summary group duplicate less. (PR#15798)
• (Unix-alikes.) system(cmd, input = ) now uses ‘shell-execution-environment’ redirection, which will be more natural if cmd is not a single command (but requires a POSIX-compliant shell). (Wish of PR#15508)
• read.fwf() and read.DIF() gain a fileEncoding argument, for convenience.
• Graphics devices can add attributes to their description in .Device and .Devices. Several of those included with R use a "filepath" attribute.
• pmatch() uses hashing in more cases and so is faster at the expense of using more memory. (PR#15697)
• pairs() gains new arguments to select sets of variables to be plotted against each other.
• file.info(, extra_cols = FALSE) allows a minimal set of columns to be computed on Unix-alikes: on some systems without properly-configured caching this can be significantly faster with large file lists.
• New function dir.exists() in package base to test efficiently whether one or more paths exist and are directories.
• dput() and friends gain new controls hexNumeric and digits17 which output double and complex quantities as, respectively, binary fractions (exactly, see sprintf("%a")) and as decimals with up to 17 significant digits.
• save(), saveRDS() and serialize() now support ascii = NA which writes ASCII files using sprintf("%a") for double/complex quantities. This is read-compatible with ascii = TRUE but avoids binary->decimal->binary conversions with potential loss of precision. Unfortunately the Windows C runtime’s lack of C99 compliance means that the format cannot be read correctly there in R before 3.1.2.
• The default for formatC(decimal.mark =) has been changed to be getOption("OutDec"); this makes it more consistent with format() and suitable for use in print methods, e.g. those for classes "density", "ecdf", "stepfun" and "summary.lm".

  getOption("OutDec") is now consulted by the print method for class "kmeans", by cut(), dendrogram(), plot.ts() and quantile() when constructing labels and for the report fromlegend(trace = TRUE).

  (In part, wish of PR#15819.)

• printNum() and hence format() and formatC() give a warning if big.mark and decimal.mark are set to the same value (period and comma are not uncommonly used for each, and this is a check that conventions have not got mixed).
• merge() can create a result which uses long vectors on 64-bit platforms.
• dget() gains a new argument keep.source which defaults to FALSE for speed (dput() and dget() are most often used for data objects where this can make dget() many times faster).
• Packages may now use a file of common macro definitions in their help files, and may import definitions from other packages.
• A number of macros have been added in the new ‘share/Rd’ directory for use in package overview help pages, and promptPackage() now makes use of them.
• tools::parse_Rd() gains a new permissive argument which converts unrecognized macros into text. This is used by utils:::format.bibentry to allow LaTeX markup to be ignored.
• options(OutDec =) can now specify a multi-byte character, e.g., options(OutDec = "u00b7") in a UTF-8 locale.
• is.recursive(x) is no longer true when x is an external pointer, a weak reference or byte code; the first enables all.equal(x, x) when x .
• ls() (aka objects()) and as.list.environment() gain a new argument sorted.
• The "source" attribute (which has not been added to functions by R since before R version 2.14.0) is no longer treated as special.
• Function returnValue() has been added to give on.exit() code access to a function’s return value for debugging purposes.
• crossprod(x, y) allows more matrix coercions when x or y are vectors, now equalling t(x) %*% y in these cases (also reported by Radford Neal). Similarly, tcrossprod(x,y) and %*% work in more cases with vector arguments.
• Utility function dynGet() useful for detecting cycles, aka infinite recursions.
• The byte-code compiler and interpreter include new instructions that allow many scalar subsetting and assignment and scalar arithmetic operations to be handled more efficiently. This can result in significant performance improvements in scalar numerical code.
• apply(m, 2, identity) is now the same as the matrix m when it has named row names.
• A new function debuggingState() has been added, allowing to temporarily turn off debugging.
• example() gets a new optional argument run.donttest and tools::Rd2ex() a corresponding commentDonttest, with a default such that example(..) in help examples will run donttest code only if used interactively (a change in behaviour).
• rbind.data.frame() gains an optional argument make.row.names, for potential speedup.
• New function extSoftVersion() to report on the versions of third-party software in use in this session. Currently reports versions of zlib, bzlib, the liblzma from xz, PCRE, ICU, TRE and the iconv implementation.

  A similar function grSoftVersion() in package grDevices reports on third-party graphics software.

  Function tcltk::tclVersion() reports the Tcl/Tk version.

• Calling callGeneric() without arguments now works with primitive generics to some extent.
• vapply(x, FUN, FUN.VALUE) is more efficient notably for large length(FUN.VALUE); as extension of PR#16061.
• as.table() now allows tables with one or more dimensions of length 0 (such as as.table(integer())).
• names(x) now clears the names of call and ... objects.
• library() will report a warning when an insufficient dependency version is masking a sufficient one later on the library search path.
• A new plot() method for class "raster" has been added.
• New check_packages_in_dir_changes() function in package tools for conveniently analyzing how changing sources impacts the check results of their reverse dependencies.
• Speed-up from Peter Haverty for ls() and methods:::.requirePackage() speeding up package loading. (PR#16133)
• New get0() function, combining exists() and get() in one call, for efficiency.
• match.call() gains an envir argument for specifying the environment from which to retrieve the ... in the call, if any; this environment was wrong (or at least undesirable) when thedefinition argument was a function.
• topenv() has been made .Internal() for speedup, based on Peter Haverty’s proposal in PR#16140.
• getOption() no longer calls options() in the main case.
• Optional use of libcurl (version 7.28.0 from Oct 2012 or later) for Internet access:
  • capabilities("libcurl") reports if this is available.
  • libcurlVersion() reports the version in use, and other details of the "libcurl" build including which URL schemes it supports.
  • curlGetHeaders() retrieves the headers for http://, https://, ftp:// and ftps:// URLs: analysis of these headers can provide insights into the ‘existence’ of a URL (it might for example be permanently redirected) and is so used in R CMD check --as-cran.
  • download.file() has a new optional method "libcurl" which will handle more URL schemes, follow redirections, and allows simultaneous downloads of multiple URLs.
  • url() has a new method "libcurl" which handles more URL schemes and follows redirections. The default method is controlled by a new option url.method, which applies also to the opening of URLs via file() (which happens implicitly in functions such as read.table.)
  • When file() or url() is invoked with a https:// or ftps:// URL which the current method cannot handle, it switches to a suitable method if one is available.
• (Windows.) The DLLs ‘internet.dll’ and ‘internet2.dll’ have been merged. In this version it is safe to switch (repeatedly) between the internal and Windows internet functions within an Rsession.

  The Windows internet functions are still selected by flag –internet2 or setInternet2(). This can be overridden for an url() connection via its new method argument.

  download.file() has new method "wininet", selected as the default by –internet2 or setInternet2().

• parent.env<- can no longer modify the parent of a locked namespace or namespace imports environment. Contributed by Karl Millar.
• New function isLoadedNamespace() for readability and speed.
• names(env) now returns all the object names of an environment env, equivalently to ls(env, all.names = TRUE, sorted = FALSE) and also to the names of the corresponding list,names(as.list(env, all.names = TRUE)). Note that although names() returns a character vector, the names have no particular ordering.
• The memory manager now grows the heap more aggressively. This reduces the number of garbage collections, in particular while data or code are loaded, at the expense of slightly increasing the memory footprint.
• New function trimws() for removing leading/trailing whitespace.
• cbind() and rbind() now consider S4 inheritance during S3 dispatch and also obey deparse.level.
• cbind() and rbind() will delegate recursively to methods::cbind2 (methods::rbind2) when at least one argument is an S4 object and S3 dispatch fails (due to ambiguity).
• (Windows.) download.file(quiet = FALSE) now uses text rather than Windows progress bars in non-interactive use.
• New function hsearch_db() in package utils for building and retrieving the help search database used by help.search(), along with functions for inspecting the concepts and keywords in the help search database.
• New function .getNamespaceInfo(), a no-check version of getNamespaceInfo() mostly for internal speedups.
• The help search system now takes keyword entries in Rd files which are not standard keywords (as given in ‘KEYWORDS’ in the R documentation directory) as concepts. For standard keyword entries the corresponding descriptions are additionally taken as concepts.
• New lengths() function for getting the lengths of all elements in a list.
• New function toTitleCase() in package tools, tailored to package titles.
• The matrix methods of cbind() and rbind() allow matrices as inputs which have 2^31 or more elements. (For cbind(), wish of PR#16198.)
• The default method of image() has an explicit check for a numeric or logical matrix (which was always required).
• URLencode() will not by default encode further URLs which appear to be already encoded.
• BIC(mod) and BIC(mod, mod2) now give non-NA numbers for arima() fitted models, as nobs(mod) now gives the number of “used” observations for such models. This fixes PR#16198, quite differently than proposed there.
• The print() methods for "htest", "pairwise.htest" and "power.htest" objects now have a digits argument defaulting to (a function of) getOption("digits"), and influencing all printed numbers coherently. Unavoidably, this changes the display of such test results in some cases.
• Code completion for namespaces now recognizes all loaded namespaces, rather than only the ones that are also attached.
• The code completion mechanism can now be replaced by a user-specified completer function, for (temporary) situations where the usual code completion is inappropriate.
• unzip() will now warn if it is able to detect truncation when unpacking a file of 4GB or more (related to PR#16243).
• methods() reports S4 in addition to S3 methods; output is simplified when the class argument is used. .S3methods() and methods::.S4methods() report S3 and S4 methods separately.
• Higher order functions such as the apply functions and Reduce() now force arguments to the functions they apply in order to eliminate undesirable interactions between lazy evaluation and variable capture in closures. This resolves PR#16093.

More at http://cran.rstudio.com/

Reference: http://www.r-bloggers.com/r-3-2-0-is-released-using-the-installr-package-to-upgrade-in-windows-os/