I had the good fortune on Thursday to hear a fascinating talk on deep transcriptome analysis by Chris Mason, Assistant Professor, at the Institute for Computational Biomedicine at Cornell University. 

Several intriguing observations were presented during the talk.  I'll present the key points first and then discuss the data.

These data concern the human transcriptome, and at least some of the results are supported by  follow on studies with data from the pigmy tailed macaque.

Some of the most interesting points from Mason's talk were:

  1. A large
  2. ... Read more
One of my hobbies lately has been to get either RNA seq or microarray data from GEO and do quick analyses. Not only is this fun, I can find good examples to use for teaching biology. One of these fun examples comes from some Arabidopsis data. In this experiment, some poor little seedlings were taken out of their happy semi-liquid culture tubes and allowed to dry out. This simulated drought situation isn't exactly dust bowls and hollow-eyed farmers, but the plants don't know that and most likely respond in a similar way. ... Read more
Is there a place for citizen scientists in the world of digital biology? Many of the citizen science projects that I've been reading about have a common structure. There's a University lab at the top, outreach educators in the middle, and a group of citizens out in the field collecting data. After the data are collected, they end up in a database somewhere and the University researchers analyze them and write papers. At least that's my impression so far. It seems to me, that with all kinds of databases out there, on-line, there should be plenty of opportunity for both citizens and student ... Read more
These days, DNA sequencing happens in one of three ways. In the early days of DNA sequencing (like the 80's), labs prepared their own samples, sequenced those samples, and analyzed their results. Some labs still do this. Then, in the 90's, genome centers came along. Genome centers are like giant factories that manufacture sequence data. They have buildings, dedicated staff, and professional bioinformaticians who write programs and work with other factory members to get the data entered, analyzed, and shipped out to the databases. (You can ... Read more
What do you call a biologist who uses bioinformatics tools to do research, but doesn't program? You don't know? Neither does anyone else. The names we use People who practice biology are known by many names, so many, that the number of names almost reflects the diversity of biology itself. Sometimes we describe biologists by the subject they study. Thus, we have biologists from anatomists to zoologists, and everything in between: addiction researchers ... Read more

I often get questions about bioinformatics, bioinformatics jobs and career paths.

Most of the questions reflect a general sense of confusion between creating bioinformatics resources and using them. Bioinformatics is unique in this sense. No one confuses writing a software package like Photoshop with being a photographer, yet for some odd reason, people seem to expect this of biologists. In the same respect, even the programmers and database administrators who work in bioinformatics, are unfairly assumed to have had graduate level training in biology.

In many ways, it's ... Read more

For many years, I've been perfectly content to work with small numbers of things. Working with one gene or one protein is great. Even small groups of genes are okay. I'm fine with alternatively spliced genes with multiple transcripts, or multiple polymorphisms, or genes in multi-gene families, or groups of genes in operons. But I never trusted microarrays. First, there were all the articles questioning the ability to reproduce microarray data. For many years, people reported difficulties in reproducing experiments, especially if they used chips from different ... Read more
For those of you who may have been wondering where I've been, these past few weeks have seen me grading final projects, writing a chapter on analyzing Next Gen DNA sequencing data for the Current Protocols series, and flying back and forth between Seattle and various meetings elsewhere in the U.S. It will probably take years of bike commuting to make up for my carbon credits, but most meetings I attend don't have viable alternatives in venues like Second Life or World of Warcraft. Anyway, as I sit writing on an airplane, I think I could revise the title for Dr. Seuss' famous book to "Oh the ... Read more

No more delays! BLAST away!

Time to blast. Let's see what it means for sequences to be similar. 

First, we'll plan our experiment.  When I think about digital biology experiments, I organize the steps in the following way: 

           A.  Defining the question

B.  Making the data sets

           C.  Analyzing the data sets

D.  Interpreting the results

I'm going intersperse my results with a few instructions so ... Read more

We'll have a blast, I promise! But there's one little thing we need to discuss first...

I want to explain why I'm going to use nucleotide sequences for the blast search. (I used protein the other day). It's not just because someone told me too, there is a solid rational reason for this.

The reason is the redundancy in the genetic code.

Okay, that probably didn't make any sense to those of you who didn't already know the answer. Here it is. ... Read more

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