<commit_before>---
layout: post
title: Wetware is Hard
date: 2016-04-11 14:19
# Should be longer than 150 words, so it will appear as post summary
description: "The life sciences carry incredible promise, but many bright researchers avoid it for faster-moving fields with better tools."
# tags will also be used as html meta keywords.
tags:
  - synthetic biology

show_meta: true
comments: true
mathjax: true
gistembed: true
published: true
noindex: false
nofollow: false
---
<div id="table-of-contents">
<h2>Table of Contents</h2>
<div id="text-table-of-contents">
<ul>
<li><a href="#orgheadline1">1. 1. Computation, Software, Automation</a></li>
<li><a href="#orgheadline2">2. 2. Reproducibility</a></li>
<li><a href="#orgheadline3">3. Let's contrast this dismal picture by an idealized one.</a></li>
</ul>
</div>
</div>

Let's talk about a couple of problems with life science that we can see by comparing
it with the rapidly-innovating field of computer science. The Silicon Valley mantra
is "hardware is hard," and we know that wetware is even harder. Biology is slow
and hard.

Nevertheless, and while admitting a possibly-naïve viewpoint, the get-it-done
impatience of computer science shows us a couple of problems in the life sciences.

### Computation, Software, Automation<a id="orgheadline1"></a>

Life science largely proceeds by hand and stores results in paper notebook.
We have pipette robots but few others. The default is to store the vast amounts of
data generated on the long trail to a published paper in hard-to-access 
and hard-to-share forms.

The cutting edge is Excel worksheets. 

### Reproducibility<a id="orgheadline2"></a>

From <NAME> and others we're familiar with the problem of positive publication
bias. A positive result is twice as likely to be published, and researchers monkey
with data sub-categories until they reach a significant result. They then restrict
access to their data so no one else can steal it.<commit_msg>Edits to A Life Decoded, post on CS vs. bio<commit_after>---
layout: post
title: Wetware is Hard
date: 2016-04-11 14:19
# Should be longer than 150 words, so it will appear as post summary
description: "The life sciences carry incredible promise, but many bright researchers avoid it for faster-moving fields with better tools. If we arbitrage techniques from other fields, the life sciences could move faster."
# tags will also be used as html meta keywords.
tags:
  - synthetic biology

show_meta: true
comments: true
mathjax: true
gistembed: true
published: true
noindex: false
nofollow: false
---
<div id="table-of-contents">
<h2>Table of Contents</h2>
<div id="text-table-of-contents">
<ul>
<li><a href="#orgheadline1">1. Computation, Software, Automation</a></li>
<li><a href="#orgheadline2">2. Reproducibility</a></li>
<li><a href="#orgheadline3">3. Let's contrast this dismal picture by an idealized one.</a></li>
</ul>
</div>
</div>

Let's talk about a couple of problems with life science that we can see by comparing
it with the rapidly-innovating field of computer science. The Silicon Valley mantra
is "hardware is hard," and we know that wetware is even harder. Biology is slow
and hard.

Nevertheless, and while admitting a possibly-naïve viewpoint, the get-it-done
impatience of computer science shows us a couple of problems in the life sciences.

### Computation, Software, Automation<a id="orgheadline1"></a>

Life science largely proceeds by hand and stores results in paper notebook.
We have pipette robots but few others. The default is to store the vast amounts of
data generated on the long trail to a published paper in hard-to-access 
and hard-to-share forms.

The cutting edge is Excel worksheets. 

### Reproducibility<a id="orgheadline2"></a>

From <NAME> and others we're familiar with the problem of positive publication
bias. A positive result is twice as likely to be published, and researchers monkey
with data sub-categories until they reach a significant result. They then restrict
access to their data so no one else can steal it.
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