<?xml version="1.0" encoding="utf-8"?>
<?xml-stylesheet type="text/xsl" href="../assets/xml/rss.xsl" media="all"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Pollard Labs Blog (Posts about Git)</title><link>https://pollardlabs.com/</link><description></description><atom:link href="https://pollardlabs.com/tags/git.xml" rel="self" type="application/rss+xml"></atom:link><language>en</language><copyright>Contents © 2022 &lt;a href="mailto:public@stephentpollard.com"&gt;Stephen Pollard&lt;/a&gt; </copyright><lastBuildDate>Sat, 16 Jul 2022 16:03:39 GMT</lastBuildDate><generator>Nikola (getnikola.com)</generator><docs>http://blogs.law.harvard.edu/tech/rss</docs><item><title>P-clouds</title><link>https://pollardlabs.com/posts/p-clouds/</link><dc:creator>Stephen Pollard</dc:creator><description>&lt;p&gt;2013 - 2016&lt;/p&gt;
&lt;p&gt;P-clouds is a methodology for identifying transposable elements in genomes and
for estimating the false positive and false negative rates of identification.
While using this program, I found a number of critical bugs in the software
that lead incorrect results. I tracked down these errors and fixed
them as they were found. I then created a number of new methods for
identification using similar ideas from P-clouds and tested their efficacy
against older methods.&lt;/p&gt;
&lt;p&gt;Associated publication:&lt;/p&gt;
&lt;ul class="simple"&gt;
&lt;li&gt;&lt;p&gt;Gu, Wanjun, et al. "Identification of repeat structure in large genomes using
repeat probability clouds." Analytical biochemistry 380.1 (2008): 77-83.&lt;/p&gt;&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;Tools: C, Perl, R, Git&lt;/p&gt;
&lt;p&gt;Repository: &lt;a class="reference external" href="https://github.com/PollockLaboratory/pclouds"&gt;https://github.com/PollockLaboratory/pclouds&lt;/a&gt;&lt;/p&gt;</description><category>C</category><category>Data science</category><category>Git</category><category>Perl</category><category>R</category><guid>https://pollardlabs.com/posts/p-clouds/</guid><pubDate>Fri, 16 Aug 2019 06:00:00 GMT</pubDate></item><item><title>Soterea Autonobox</title><link>https://pollardlabs.com/posts/autonobox/</link><dc:creator>Stephen Pollard</dc:creator><description>&lt;p&gt;2016&lt;/p&gt;
&lt;p&gt;Soterea develops safety devices for commercial vehicles. The Autonobox was a
product mounted to the front of large trucks to predict a possible collision
and automatically brake the truck before the collision occurs. The product
consisted of a radar array attached to the front of the truck and controllers
linked to the braking system. I worked on the algorithm testing framework for
evaluating multiple algorithms against many different possible scenarios. I
developed a file format and language for encoding scenarios to be tested. I
rewrote the scenario visualization GUI in Python which was previously written
in Java. I produced multiple algorithms for predicting collisions given the
radar input data and successfully tested them against the set of developed
scenarios. I also contributed to the C software compiled for the
microcontroller which ran the Autonobox product.&lt;/p&gt;
&lt;p&gt;Tools: C, C++, Python, Qt, Git&lt;/p&gt;
&lt;p&gt;Website: &lt;a class="reference external" href="http://www.soterea.com/"&gt;http://www.soterea.com/&lt;/a&gt;&lt;/p&gt;</description><category>C</category><category>C++</category><category>Git</category><category>Python</category><category>Qt</category><guid>https://pollardlabs.com/posts/autonobox/</guid><pubDate>Fri, 16 Aug 2019 06:00:00 GMT</pubDate></item></channel></rss>