Botcasting: Listening to your Journal Feeds

If you’ve worked at a lab before, you’ve no doubt noticed a certain rhythm to the day. People come in early, setup their experiments, and by 10 the experiments for the day are underway, and the scientists are working on email (or Facebook), or are in the gym or are in the midst of a morning run around campus.  In the afternoons you may have followup experiments, cleanup, and data analysis tasks to do.  Walking through any lab, you’ll find people running experiments and listening to music, or podcasts on their phones or iPods as they work.  And then there are those wasted blocks of time for your daily commute that bookend your day. In fact, throughout every day there are these snippets of time that could be used to keep up to date with the latest developments in a field.

So how could you use that time more effectively? What if you could listen to the RSS feeds of your favorite journals? Well, there’s a technology called Botcasting that can help you do that. The term is a portmanteau: “robot + broadcasting” that was coined a number of years ago when the underlying Text To Speech (TTS) technology was rolled out on desktops and phones.  The initial voices were very robotic.

In my previous posting, I showed how I use Pocket to save papers, and articles to read later.  The Pocket Android app has a neat feature called “Listen” that reads any article you’ve pocketed back to you.  This is really useful, when you need to have your hands free, but want to learn something while you’re working.  You simply open an article that you’ve pocketed, and select “Listen (TTS)” from the menu, and Pocket will begin reading the article to you.  You can select from a number of different voices to change the listening experience.  If you’re an iPhone user, the LisGo app performs a similar function.

In addition to using TTS technology on your phone, it is also available on most operating systems.  In Mac OS X, it’s implemented as a service, and integrated into your browser.  When you find an article that you want to read later, you simply select the text of the article, and right-click and select the “Add to iTunes as a Spoken Track”.  A dialog box will pop up asking you where to save it and what voice to use when speaking it.  I use the Victoria voice which sounds more human than the others.  If you open up iTunes, you’ll find the file listed under Music.  You can then queue up a bunch of these tracks and listen to them at your leisure.  Or sync them with your iPod and listen to them in the Lab.

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A Pocketful of Rye

Unlike the Agatha Christie mystery referred to in the title of this piece, there are some mysteries that seem to defy a single answer.  One of those mysteries is how most scientists manage to keep up-to-date given the growing avalanche of developments in their fields. The answers I get are wide and varied, but I thought I would share a couple variations on my workflows, and perhaps start a conversation at the same time.

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Google IO, Schemas, and the Network of BioThings

Last week’s Google IO conference came with a slew of announcements, and videos, but perhaps the most interesting idea, wasn’t accompanied by a flashy announcement.  It did have some intriguing video’s though.  The first of which is shown below.

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Network of BioThings: Making PDFs Useful

Recently, Andrew Su of Scripps posted a series of blog entries on the Network of Biothings (NoB) efforts, especially their efforts to uncover use cases that could aid medical research. In a nutshell,”The Network of BioThings aims to structure the biological knowledge found in biomedical research articles by comprehensively annotating BioThings (genes, proteins, mutations, diseases, drugs, etc.) in a timely fashion (one week after publication). This would allow for focused browsing as well as large-scale data mining.”[1]

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JavaScript Libraries for Informatics

During our monthly San Diego Informatics Lunch meeting, the topic of conversation was JavaScript libraries for informatics.  Over the past few years the term “thick client application” has gradually morphed from a reference to desktop applications, to JavaScript-heavy browser-based applications.  Driven in part by libraries like jQuery, Angular.js, Backbone.js, and Ember, these frameworks (along with the adoption of HTML5) have enabled applications that weren’t previously possible in a browser.

Kei Ono, lead developer from UCSD’s Cytoscape project, remarked that at a recent meeting on visualization, there were no projects with desktop applications.

In preparation for the meeting, I did a brief survey of JavaScript libraries with the following results:

BioJS – Built by the folks at EBI, BioJS provides a series of components for visualizing sequence and structure information.  Here’s a video from last year’s GMOD meeting that describes the project.

ChemWriter – built by MetaMolecular, this pure JavaScript library makes it possible to edit 2D chemical structures.

Cytoscape.js - The Cytoscape.js framework provides a means for visualizing networked biological data in a browser.  With the latest release of the Cytoscape Java application you can now export network data in JSON format, and visualize it in a web page using the Cytoscape.js library.

jBio – referring to itself as “BioPerl in JavaScript”, jBio is a jQuery-based library for manipulating and visualizing sequence data.

JBrowse – This library makes it easy to create your own genome browser.

jsMol – Is a transpiled version of jMol that allows users to view 3D molecular structures without having Java installed.

jsMolEdit – a library for editing and viewing 2D chemical structures. The library makes use of GWT.

jsPhylosvgis a library for rendering phylogenetic trees.

OneZoom – another library for rendering phylogenetic trees.

Scribl – is a JavaScript library for visualizing “genomic regions, alignments and assembly data”.

SMS – The rather unfortunately named, Sequence Manipulation Suite, is a library for manipulating sequence data.

By-and-large, the JavaScript components were dedicated to visualizing data in the browser.  If anyone has a library that they’d like to add to the list, leave a comment below.

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Tinkering With Semantic Markup

One of the key challenges for bioinformaticians in this age is extracting meaningful findings from abstracts and full text articles. Text mining solutions can only take it so far, and previous comparative studies have shown that Amazon Mechanical Turk solutions and automated text mining solutions have similar levels of success when it comes to identifying terms in text and attaching some kind of semantic meaning them.

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Advanced PubMed Searching

US-NLM-PubMed-LogoIn previous postings (listed at the bottom of the article), I described some of the advanced features in PubMed that you can use to quickly narrow the field of your search in PubMed.  Recently I started working on some updates to BioGroovy’s PubMedSearch engine which led me to take a closer look at some of these advanced search capabilities. Here are a few of the fields that proved to be more useful in my own searches:

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