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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/40489?offset=0</link>
	<atom:link href="https://bioinformaticsonline.com/related/40489?offset=0" rel="self" type="application/rss+xml" />
	<description><![CDATA[]]></description>
	
	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial</guid>
	<pubDate>Wed, 21 May 2014 12:50:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial</link>
	<title><![CDATA[A Brief Bioinformatics Tutorial]]></title>
	<description><![CDATA[<p>This is about how to use a computer to find what is known about a gene of interest and also how to get new insights about it.</p>
<p>The tutorial is divided in three main parts:</p>
<ul>
<li>In the <strong>Sequence </strong>part, you will see how to look efficiently for a particular protein sequence, how to blast it against the database of your choice to find homologues, how to perform a multiple alignment of the homologues you've selected and how to edit this alignment.</li>
<li>The <strong>Structure </strong>part is about molecular visualization, homology modeling and structural domain prediction.</li>
<li>In the <strong>Function </strong>part, you will be introduced to you 3 useful servers to investigate the function of a protein. i.e. finding interactors, co-expressed genes, see a phylogenetic profile, easily access papers citing your gene etc ...</li>
</ul>
<p>During all the three parts, we will use the <em>S. cerevisiae </em>VPS36 protein as an example.</p><p>Address of the bookmark: <a href="http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html" rel="nofollow">http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/43817/bioinfo-lab</guid>
  <pubDate>Fri, 04 Mar 2022 00:17:00 -0600</pubDate>
  <link></link>
  <title><![CDATA[Bioinfo Lab]]></title>
  <description><![CDATA[
<p>The Institute of Bioinformatics conducts internationally renowned research and provides profound education in bioinformatics. Its research focuses on development and application of machine learning and statistical methods in biology and medicine.</p>

<p>Contact:<br />Computer Science Building (Science Park 3)<br />Altenberger Str. 69, A-4040 Linz, Austria<br />Tel. +43 732 2468 4520 / Fax +43 732 2468 4539<br />E-mail secretary@bioinf.jku.at</p>

<p>http://www.bioinf.jku.at/</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</guid>
	<pubDate>Wed, 20 Aug 2014 22:09:21 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/14218/pimp-your-brain-bioinformatics</link>
	<title><![CDATA[Pimp your brain: Bioinformatics]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/KqelGy6Q8nE" frameborder="0" allowfullscreen></iframe>Jan Lisec from the Max Planck Institute of Molecular Plant Physiology explains, in this "pimp your brain" episode, what bioinformatics is and why bioinformatics is so important and indispensable for biological research.

In the video serial "Pimp your brain" scientists from the Max Planck Institute of Molecular Plant Physiology describe their research. More videos from the 'Pimp your brain' serial are available on www.youtube.com/playlist?list=PL-l9VItC9Gn2Ur2Xj6PTOAkjLUlVPbIOO

More videos are available on www.mpimp-golm.mpg.de]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43369/a-guide-to-machine-learning-for-biologists</guid>
	<pubDate>Wed, 15 Sep 2021 13:21:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43369/a-guide-to-machine-learning-for-biologists</link>
	<title><![CDATA[A guide to machine learning for biologists]]></title>
	<description><![CDATA[<p><span>We aim to provide readers with a gentle introduction to a few key machine learning techniques, including the most recently developed and widely used techniques involving deep neural networks. We describe how different techniques may be suited to specific types of biological data, and also discuss some best practices and points to consider when one is embarking on experiments involving machine learning. Some emerging directions in machine learning methodology are also&nbsp;discussed.</span></p><p>Address of the bookmark: <a href="https://www.nature.com/articles/s41580-021-00407-0" rel="nofollow">https://www.nature.com/articles/s41580-021-00407-0</a></p>]]></description>
	<dc:creator>LEGE</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/12787/integrative-genomics-viewer-igv-tutorial</guid>
	<pubDate>Sat, 12 Jul 2014 15:16:23 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/12787/integrative-genomics-viewer-igv-tutorial</link>
	<title><![CDATA[Integrative Genomics Viewer (IGV) tutorial]]></title>
	<description><![CDATA[<p>The <a href="http://www.broadinstitute.org/igv/">Integrative Genomics Viewer (IGV)</a> from the Broad Center allows you to view several types of data files involved in any NGS analysis that employs a reference genome, including how reads from a dataset are mapped, gene annotations, and predicted genetic variants.</p>
<p>http://www.broadinstitute.org/igv/</p><p>Address of the bookmark: <a href="https://wikis.utexas.edu/display/bioiteam/Integrative+Genomics+Viewer+%28IGV%29+tutorial" rel="nofollow">https://wikis.utexas.edu/display/bioiteam/Integrative+Genomics+Viewer+%28IGV%29+tutorial</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/21444/a-guide-for-complete-r-beginners-installing-r-packages</guid>
	<pubDate>Tue, 24 Feb 2015 20:23:34 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/21444/a-guide-for-complete-r-beginners-installing-r-packages</link>
	<title><![CDATA[A guide for complete R beginners :- Installing R packages]]></title>
	<description><![CDATA[<p>Part of the reason R has become so popular is the vast array of packages available at the <a href="http://cran.r-project.org/" target="_blank">cran</a> and <a href="http://www.bioconductor.org/" target="_blank">bioconductor</a> repositories. In the last few years, the number of packages has grown <a href="http://blog.revolutionanalytics.com/2010/09/what-can-other-languages-learn-from-r.html" target="_blank">exponentially</a>!</p><p>This is a short post giving steps on how to actually install R packages. Let&rsquo;s suppose you want to install the <a href="http://had.co.nz/ggplot2/" target="_blank">ggplot2</a> package. Well nothing could be easier. We just fire up an R shell and type:<br /><code><br />&gt; install.packages("ggplot2")</code></p><p>In theory the package should just install, however:</p><ul>
<li>if you are using Linux and don&rsquo;t have root access, this command won&rsquo;t work.</li>
<li>you will be asked to select your local mirror, i.e. which server should you use to download the package.</li>
</ul><h4>Installing packages without root access</h4><p>First, you need to designate a directory where you will store the downloaded packages. On my machine, I use the directory <code>/data/Rpackages/</code> After creating a package directory, to install a package we use the command:<br /><code><br />&gt; install.packages("ggplot2"</code><code>, lib="/data/Rpackages/")<br />&gt; library(ggplot2, lib.loc="/data/Rpackages/")<br /></code></p><p>It&rsquo;s a bit of a pain having to type <code>/data/Rpackages/</code> all the time. To avoid this burden,&nbsp; we create a file <code>.Renviron</code> in our home area, and add the line <code>R_LIBS=/data/Rpackages/</code> to it. This means that whenever you start R, the directory <code>/data/Rpackages/</code> is added to the list of places to look for R packages and so:</p><p><code>&gt; install.packages("ggplot2"</code><code>)<br />&gt; library(ggplot2)</code></p><p>just works!</p><h4>Setting the repository</h4><p>Every time you install a R package, you are asked which repository R should use. To set the repository and avoid having to specify this at every package install, simply:</p><ul>
<li>create a file <code>.Rprofile</code> in your home area.</li>
<li>Add the following piece of code to it:</li>
</ul><p><code><br />cat(".Rprofile: Setting UK repositoryn")<br />r = getOption("repos") # hard code the UK repo for CRAN<br />r["CRAN"] = "http://cran.uk.r-project.org"<br />options(repos = r)<br />rm(r)<br /></code></p><p>I found this tip in a stackoverflow <a href="http://stackoverflow.com/questions/1189759/expert-r-users-whats-in-your-rprofile/1189826#1189826" target="_blank">answer </a>.</p>]]></description>
	<dc:creator>Archana Malhotra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/22133/r-320-is-released</guid>
	<pubDate>Sat, 18 Apr 2015 05:06:44 -0500</pubDate>
	<link>https://bioinformaticsonline.com/news/view/22133/r-320-is-released</link>
	<title><![CDATA[R 3.2.0 is released]]></title>
	<description><![CDATA[<p>R 3.2.0 (codename &ldquo;Full of Ingredients&rdquo;)&nbsp;was <a href="http://r.789695.n4.nabble.com/R-3-2-0-is-released-td4705933.html" target="_blank">released yesterday</a>.&nbsp;You can get the latest binaries version <strong><a href="http://cran.rstudio.com/" target="_blank">from here</a>.</strong>&nbsp;(or the .tar.gz&nbsp;<strong>source</strong> code from <a href="http://cran.r-project.org/src/base/R-3/R-3.2.0.tar.gz" target="_blank">here</a>).&nbsp;The full list of new features and bug fixes is provided below.</p><h3>Upgrading to R 3.2.0 on Windows</h3><p>If you are using <strong>Windows&nbsp;</strong>you can easily upgrade to the latest version of R using <a href="http://cran.r-project.org/web/packages/installr/" target="_blank">the installr package</a>. Simply run the following code:</p><div><table>
<tbody>
<tr id="p612572">
<td id="p61257code2">
<pre><span style="color: #228b22;"># installing/loading the latest installr package:</span>
<span style="color: #0000ff; font-weight: bold;">install.<span>packages</span></span><span style="color: #080;">(</span><span style="color: #ff0000;">"installr"</span><span style="color: #080;">)</span><span style="color: #080;">;</span> <span style="color: #0000ff; font-weight: bold;">library</span><span style="color: #080;">(</span>installr<span style="color: #080;">)</span> <span style="color: #228b22;">#load / install+load installr</span>
&nbsp;
updateR<span style="color: #080;">(</span><span style="color: #080;">)</span> <span style="color: #228b22;"># updating R.</span></pre>
</td>
</tr>
</tbody>
</table></div><p><span>Running &ldquo;updateR()&rdquo; will detect if there is a new R version available, and if so it will download+install it (etc.).</span></p><p><span><strong>If you are an R blogger yourself</strong> you are invited to <a href="http://www.r-bloggers.com/add-your-blog/">add your own R content feed to this site</a> (<strong>Non-English</strong> R bloggers should add themselves- <a href="http://www.r-bloggers.com/lang/add-your-blog">here</a>)</span></p><h4>NEW FEATURES</h4><ul>
<li><code>anyNA()</code> gains a <code>recursive</code> argument.</li>
<li>When <code>x</code> is missing and <code>names</code> is not false (including the default value), <code>Sys.getenv(x, names)</code> returns an object of class <code>"Dlist"</code> and hence prints tidily.</li>
<li>(Windows.) <code>shell()</code> no longer consults the environment variable <span>SHELL</span>: too many systems have been encountered where it was set incorrectly (usually to a path where software was compiled, not where it was installed). <span>R_SHELL</span>, the preferred way to select a non-default shell, can be used instead.</li>
<li>Some unusual arguments to <code>embedFonts()</code> can now be specified as character vectors, and the defaults have been changed accordingly.</li>
<li>Functions in the <code>Summary</code> group duplicate less. (<a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15798" target="_blank">PR#15798</a>)</li>
<li>(Unix-alikes.) <code>system(cmd, input = )</code> now uses &lsquo;shell-execution-environment&rsquo; redirection, which will be more natural if <code>cmd</code> is not a single command (but requires a POSIX-compliant shell). (Wish of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15508" target="_blank">PR#15508</a>)</li>
<li><code>read.fwf()</code> and <code>read.DIF()</code> gain a <code>fileEncoding</code> argument, for convenience.</li>
<li>Graphics devices can add attributes to their description in <code>.Device</code> and <code>.Devices</code>. Several of those included with <strong>R</strong> use a <code>"filepath"</code> attribute.</li>
<li><code>pmatch()</code> uses hashing in more cases and so is faster at the expense of using more memory. (<a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15697" target="_blank">PR#15697</a>)</li>
<li><code>pairs()</code> gains new arguments to select sets of variables to be plotted against each other.</li>
<li><code>file.info(, extra_cols = FALSE)</code> 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.</li>
<li>New function <code>dir.exists()</code> in package <span>base</span> to test efficiently whether one or more paths exist and are directories.</li>
<li><code>dput()</code> and friends gain new controls <span>hexNumeric</span> and <span>digits17</span> which output double and complex quantities as, respectively, binary fractions (exactly, see <code>sprintf("%a")</code>) and as decimals with up to 17 significant digits.</li>
<li><code>save()</code>, <code>saveRDS()</code> and <code>serialize()</code> now support <code>ascii = NA</code> which writes ASCII files using <code>sprintf("%a")</code> for double/complex quantities. This is read-compatible with <code>ascii = TRUE</code> but avoids binary-&gt;decimal-&gt;binary conversions with potential loss of precision. Unfortunately the Windows C runtime&rsquo;s lack of C99 compliance means that the format cannot be read correctly there in <strong>R</strong> before 3.1.2.</li>
<li>The default for <code>formatC(decimal.mark =)</code> has been changed to be <code>getOption("OutDec")</code>; this makes it more consistent with <code>format()</code> and suitable for use in print methods, e.g. those for classes <code>"density"</code>, <code>"ecdf"</code>, <code>"stepfun"</code> and <code>"summary.lm"</code>.
<p><code>getOption("OutDec")</code> is now consulted by the print method for class <code>"kmeans"</code>, by <code>cut()</code>, <code>dendrogram()</code>, <code>plot.ts()</code> and <code>quantile()</code> when constructing labels and for the report from<code>legend(trace = TRUE)</code>.</p>
<p>(In part, wish of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=15819" target="_blank">PR#15819</a>.)</p>
</li>
<li><code>printNum()</code> and hence <code>format()</code> and <code>formatC()</code> give a warning if <code>big.mark</code> and <code>decimal.mark</code> 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).</li>
<li><code>merge()</code> can create a result which uses long vectors on 64-bit platforms.</li>
<li><code>dget()</code> gains a new argument <code>keep.source</code> which defaults to <code>FALSE</code> for speed (<code>dput()</code> and <code>dget()</code> are most often used for data objects where this can make <code>dget()</code> many times faster).</li>
<li>Packages may now use a file of common macro definitions in their help files, and may import definitions from other packages.</li>
<li>A number of macros have been added in the new &lsquo;<span>share/Rd</span>&rsquo; directory for use in package overview help pages, and <code>promptPackage()</code> now makes use of them.</li>
<li><code>tools::parse_Rd()</code> gains a new <code>permissive</code> argument which converts unrecognized macros into text. This is used by <code>utils:::format.bibentry</code> to allow LaTeX markup to be ignored.</li>
<li><code>options(OutDec =)</code> can now specify a multi-byte character, e.g., <code>options(OutDec = "u00b7")</code> in a UTF-8 locale.</li>
<li><code>is.recursive(x)</code> is no longer true when <code>x</code> is an external pointer, a weak reference or byte code; the first enables <code>all.equal(x, x)</code> when <code>x .</code></li>
<li><code>ls()</code> (aka <code>objects()</code>) and <code>as.list.environment()</code> gain a new argument <code>sorted</code>.</li>
<li>The <code>"source"</code> attribute (which has not been added to functions by <strong>R</strong> since before <strong>R</strong> version 2.14.0) is no longer treated as special.</li>
<li>Function <code>returnValue()</code> has been added to give <code>on.exit()</code> code access to a function&rsquo;s return value for debugging purposes.</li>
<li><code>crossprod(x, y)</code> allows more matrix coercions when <code>x</code> or <code>y</code> are vectors, now equalling <code>t(x) %*% y</code> in these cases (also reported by Radford Neal). Similarly, <code>tcrossprod(x,y)</code> and <code>%*%</code> work in more cases with vector arguments.</li>
<li>Utility function <code>dynGet()</code> useful for detecting cycles, aka infinite recursions.</li>
<li>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.</li>
<li><code>apply(m, 2, identity)</code> is now the same as the matrix <code>m</code> when it has <em>named</em> row names.</li>
<li>A new function <code>debuggingState()</code> has been added, allowing to temporarily turn off debugging.</li>
<li><code>example()</code> gets a new optional argument <code>run.donttest</code> and <code>tools::Rd2ex()</code> a corresponding <code>commentDonttest</code>, with a default such that <code>example(..)</code> in help examples will run <code>donttest</code> code only if used interactively (a change in behaviour).</li>
<li><code>rbind.data.frame()</code> gains an optional argument <code>make.row.names</code>, for potential speedup.</li>
<li>New function <code>extSoftVersion()</code> to report on the versions of third-party software in use in this session. Currently reports versions of <code>zlib</code>, <code>bzlib</code>, the <code>liblzma</code> from <code>xz</code>, PCRE, ICU, TRE and the <code>iconv</code> implementation.
<p>A similar function <code>grSoftVersion()</code> in package <span>grDevices</span> reports on third-party graphics software.</p>
<p>Function <code>tcltk::tclVersion()</code> reports the Tcl/Tk version.</p>
</li>
<li>Calling <code>callGeneric()</code> without arguments now works with primitive generics to some extent.</li>
<li><code>vapply(x, FUN, FUN.VALUE)</code> is more efficient notably for large <code>length(FUN.VALUE)</code>; as extension of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16061" target="_blank">PR#16061</a>.</li>
<li><code>as.table()</code> now allows tables with one or more dimensions of length 0 (such as <code>as.table(integer())</code>).</li>
<li><code>names(x) now clears the names of call and <code>...</code> objects.</code></li>
<li><code>library()</code> will report a warning when an insufficient dependency version is masking a sufficient one later on the library search path.</li>
<li>A new <code>plot()</code> method for class <code>"raster"</code> has been added.</li>
<li>New <code>check_packages_in_dir_changes()</code> function in package <span>tools</span> for conveniently analyzing how changing sources impacts the check results of their reverse dependencies.</li>
<li>Speed-up from Peter Haverty for <code>ls()</code> and <code>methods:::.requirePackage()</code> speeding up package loading. (<a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16133" target="_blank">PR#16133</a>)</li>
<li>New <code>get0()</code> function, combining <code>exists()</code> and <code>get()</code> in one call, for efficiency.</li>
<li><code>match.call()</code> gains an <code>envir</code> argument for specifying the environment from which to retrieve the <code>...</code> in the call, if any; this environment was wrong (or at least undesirable) when the<code>definition</code> argument was a function.</li>
<li><code>topenv()</code> has been made <code>.Internal()</code> for speedup, based on Peter Haverty&rsquo;s proposal in <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16140" target="_blank">PR#16140</a>.</li>
<li><code>getOption()</code> no longer calls <code>options()</code> in the main case.</li>
<li>Optional use of <code>libcurl</code> (version 7.28.0 from Oct 2012 or later) for Internet access:
<ul>
<li><code>capabilities("libcurl")</code> reports if this is available.</li>
<li><code>libcurlVersion()</code> reports the version in use, and other details of the <code>"libcurl"</code> build including which URL schemes it supports.</li>
<li><code>curlGetHeaders()</code> retrieves the headers for <code>http://</code>, <code>https://</code>, <code>ftp://</code> and <code>ftps://</code> URLs: analysis of these headers can provide insights into the &lsquo;existence&rsquo; of a URL (it might for example be permanently redirected) and is so used in <code>R CMD check --as-cran</code>.</li>
<li><code>download.file()</code> has a new optional method <code>"libcurl"</code> which will handle more URL schemes, follow redirections, and allows simultaneous downloads of multiple URLs.</li>
<li><code>url()</code> has a new method <code>"libcurl"</code> which handles more URL schemes and follows redirections. The default method is controlled by a new option <code>url.method</code>, which applies also to the opening of URLs <em>via</em> <code>file()</code> (which happens implicitly in functions such as <code>read.table</code>.)</li>
<li>When <code>file()</code> or <code>url()</code> is invoked with a <code>https://</code> or <code>ftps://</code> URL which the current method cannot handle, it switches to a suitable method if one is available.</li>
</ul>
</li>
<li>(Windows.) The DLLs &lsquo;<span>internet.dll</span>&rsquo; and &lsquo;<span>internet2.dll</span>&rsquo; have been merged. In this version it is safe to switch (repeatedly) between the internal and Windows internet functions within an <strong>R</strong>session.
<p>The Windows internet functions are still selected by flag <span>&ndash;internet2</span> or <code>setInternet2()</code>. This can be overridden for an <code>url()</code> connection <em>via</em> its new <code>method</code> argument.</p>
<p><code>download.file()</code> has new method <code>"wininet"</code>, selected as the default by <span>&ndash;internet2</span> or <code>setInternet2()</code>.</p>
</li>
<li><code>parent.env&lt;-</code> can no longer modify the parent of a locked namespace or namespace imports environment. Contributed by Karl Millar.</li>
<li>New function <code>isLoadedNamespace()</code> for readability and speed.</li>
<li><code>names(env)</code> now returns all the object names of an <code>environment</code> <code>env</code>, equivalently to <code>ls(env, all.names = TRUE, sorted = FALSE)</code> and also to the names of the corresponding list,<code>names(as.list(env, all.names = TRUE))</code>. Note that although <code>names()</code> returns a character vector, the names have no particular ordering.</li>
<li>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.</li>
<li>New function <code>trimws()</code> for removing leading/trailing whitespace.</li>
<li><code>cbind()</code> and <code>rbind()</code> now consider S4 inheritance during S3 dispatch and also obey <code>deparse.level</code>.</li>
<li><code>cbind()</code> and <code>rbind()</code> will delegate recursively to <code>methods::cbind2</code> (<code>methods::rbind2</code>) when at least one argument is an S4 object and S3 dispatch fails (due to ambiguity).</li>
<li>(Windows.) <code>download.file(quiet = FALSE)</code> now uses text rather than Windows progress bars in non-interactive use.</li>
<li>New function <code>hsearch_db()</code> in package <span>utils</span> for building and retrieving the help search database used by <code>help.search()</code>, along with functions for inspecting the concepts and keywords in the help search database.</li>
<li>New function <code>.getNamespaceInfo()</code>, a no-check version of <code>getNamespaceInfo()</code> mostly for internal speedups.</li>
<li>The help search system now takes <span>keyword</span> entries in Rd files which are not standard keywords (as given in &lsquo;<span>KEYWORDS</span>&rsquo; in the <strong>R</strong> documentation directory) as concepts. For standard keyword entries the corresponding descriptions are additionally taken as concepts.</li>
<li>New <code>lengths()</code> function for getting the lengths of all elements in a list.</li>
<li>New function <code>toTitleCase()</code> in package <span>tools</span>, tailored to package titles.</li>
<li>The matrix methods of <code>cbind()</code> and <code>rbind()</code> allow matrices as inputs which have <em>2^31</em> or more elements. (For <code>cbind()</code>, wish of <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16198" target="_blank">PR#16198</a>.)</li>
<li>The default method of <code>image()</code> has an explicit check for a numeric or logical matrix (which was always required).</li>
<li><code>URLencode()</code> will not by default encode further URLs which appear to be already encoded.</li>
<li><code>BIC(mod)</code> and <code>BIC(mod, mod2)</code> now give non-NA numbers for <code>arima()</code> fitted models, as <code>nobs(mod)</code> now gives the number of &ldquo;used&rdquo; observations for such models. This fixes <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16198" target="_blank">PR#16198</a>, quite differently than proposed there.</li>
<li>The <code>print()</code> methods for <code>"htest"</code>, <code>"pairwise.htest"</code> and <code>"power.htest"</code> objects now have a <code>digits</code> argument defaulting to (a function of) <code>getOption("digits")</code>, and influencing all printed numbers coherently. Unavoidably, this changes the display of such test results in some cases.</li>
<li>Code completion for namespaces now recognizes all loaded namespaces, rather than only the ones that are also attached.</li>
<li>The code completion mechanism can now be replaced by a user-specified completer function, for (temporary) situations where the usual code completion is inappropriate.</li>
<li><code>unzip()</code> will now warn if it is able to detect truncation when unpacking a file of 4GB or more (related to <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16243" target="_blank">PR#16243</a>).</li>
<li><code>methods()</code> reports S4 in addition to S3 methods; output is simplified when the <code>class</code> argument is used. <code>.S3methods()</code> and <code>methods::.S4methods()</code> report S3 and S4 methods separately.</li>
<li>Higher order functions such as the <code>apply</code> functions and <code>Reduce()</code> now force arguments to the functions they apply in order to eliminate undesirable interactions between lazy evaluation and variable capture in closures. This resolves <a href="https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16093" target="_blank">PR#16093</a>.</li>
</ul><p>More at http://cran.rstudio.com/</p><p>Reference: http://www.r-bloggers.com/r-3-2-0-is-released-using-the-installr-package-to-upgrade-in-windows-os/</p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26559/microscope</guid>
	<pubDate>Fri, 04 Mar 2016 05:26:31 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26559/microscope</link>
	<title><![CDATA[Microscope]]></title>
	<description><![CDATA[<p>Microscope Platform user documentation.</p>
<p>The MicroScope platform is available at this URL:</p>
<p><a href="https://www.genoscope.cns.fr/agc/microscope">https://www.genoscope.cns.fr/agc/microscope</a></p><p>Address of the bookmark: <a href="http://microscope.readthedocs.org/en/latest/index.html" rel="nofollow">http://microscope.readthedocs.org/en/latest/index.html</a></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26414/advanced-bash-scripting-guide</guid>
	<pubDate>Thu, 18 Feb 2016 04:50:51 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26414/advanced-bash-scripting-guide</link>
	<title><![CDATA[Advanced Bash-Scripting Guide]]></title>
	<description><![CDATA[<p>This tutorial assumes no previous knowledge of scripting or programming, yet progresses rapidly toward an intermediate/advanced level of instruction <em>. . . all the while sneaking in little nuggets of <span>UNIX</span>&reg; wisdom and lore</em>. It serves as a textbook, a manual for self-study, and as a reference and source of knowledge on shell scripting techniques. The exercises and heavily-commented examples invite active reader participation, under the premise that <tt><strong>the only way to really learn scripting is to write scripts</strong></tt>.</p>
<p>This book is suitable for classroom use as a general introduction to programming concepts.</p>
<p>More at http://tldp.org/LDP/abs/html/</p><p>Address of the bookmark: <a href="http://tldp.org/LDP/abs/html/" rel="nofollow">http://tldp.org/LDP/abs/html/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26972/understanding-fastqc-output</guid>
	<pubDate>Fri, 15 Apr 2016 05:47:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26972/understanding-fastqc-output</link>
	<title><![CDATA[Understanding Fastqc Output]]></title>
	<description><![CDATA[<p>Understanding Following table and graphs</p>
<ol>
<li>Duplication level</li>
<li>kmer profile</li>
<li>per base GC content</li>
<li>per base N content</li>
<li>per base quality</li>
<li>per base sequence content</li>
<li>per sequence GC content</li>
<li>per sequence quality</li>
<li>sequence length distribution</li>
</ol>
<p>More at http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/</p><p>Address of the bookmark: <a href="http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/" rel="nofollow">http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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