Cavalcade of Mammals

Notes on some bioinformatics books from two perspectives. Here’s what I’m looking for: 1) advanced discussion of computational and statistical methods for genomics, especially microarray analysis, and 2) suitability for an intro and survey bioinformatics course I teach.

THE ANALYSIS OF GENE EXPRESSION DATA: METHODS AND SOFTWARE
edited by Giovanni Parmigiani, Elizabeth S Garrett, Rafael A Irizarry, Scott L Zeger
companion website
Great medium depth howto. Covers R, dChip, SAM, and packages that take more sophisticated approaches to analysis, clustering, and visualization.

Bioinformatics for Geneticists
Edited by Michael R. Barnes and Ian C. Gray
Published Online: 22 May 2003
Genomic orientation, but too light and introductory for my needs, too genomic focused for my course. Good starting point book for a geneticist.

Advances in Systems Biology
Series: Advances in Experimental Medicine and Biology, Vol. 547
Opresko, Lee K.; Gephart, Julie M.; Mann, Michaela B. (Eds.)
2004
Pulled this book for A Systems Approach to Discovering Signaling and Regulatory Pathways—or how to digest large interaction networks into relevant pieces by Trey Ideker.

Microarray Gene Expression Data Analysis: A Beginners Guide
by Helen C. Causton , John Quackenbush , Alvis Brazma
2003
What it says it is: design, image processing, normalization, basic stats, clustering.

Bioinformatics: Databases and Systems
Edited by Stan Letovsky
Kluwer Academic Press, Boston, 1999
A chapter a database. Covers the usual gang, plus chapters on WIT/WIT2, KEGG, BioWidgets (Java), and AceDB (overview).

Statistical Methods in Bioinformatics An Introduction
Series: Statistics for Biology and Health
Ewens, Warren J. and Grant, Gregory
2nd ed. , 2004, 588p
errata
Heavy statistical treatment of sequence analysis. Starts with stats, then stat properties of one seq, multiple seq alignments, BLAST, Marlov chains, HMMs.

‘In Silico’ Simulation of Biological Processes
No. 247 Novartis Foundation Symposium
270 pages January 2003
Picked this up for the GO chapter. Also has a chapter on KEGG.

Micr
oarrays Methods and Applications: Nuts and Bolts
Edited by Gary Hardiman
2003
Covers topics from basic MA howtos to more specialized applications. A mixed bag. One chapter on microarray scanner evaluation, another on C. elegans 50-mer oligos made by the Hardiman lab at UCSD. Chapter text and figures are online.

Microarray Quality Control
by Wei Zhang, Ilya Shmulevich and Jaakko Astola
136 pages February 2004
What the title says. Microarrays from a core facility perspective. Ends with normatization. Covers long oligo design.

Microarray Bioinformatics
by Dov Stekel
Cambridge University Press. 2003
Thorough and clear coverage of microarray design, construction, image proc, and normalization. What caught my eye was the chapter on oilgo design, but its all good. Best single book on microarrays I’ve seen.

Bioinformatics: Methods and Protocols
Edited by Stephen Misener, Stephen A. Krawetz
Humana Press; 1st edition 2000
Program based by chapter. Too program based for a course. Has good chpaters on Clustal and Phylip. A chapter on Trascription control regions using MatInspector/GenomeInspector, weight matrix based sequence scanning for single or paired binding sites.

Computational Molecular Biology: an Algorithmic Approach
by Pavel A. Pevzner
MIT Press, 2000
Takes a unique approach. Looks at interesting computational aspects of seqeunce-based biology, and sometimes takes an odd sideways view of problems, getting deep into the underlying mathematics. A great complement to a more straightforward survey book. The topic coverage isn’t broad enough for my course, and the topics get covered in more depth than I need. Runs thorugh algorithmics of restircition digests to microarrays including, of course, sequencing by hybridization. Covers algorithmics of genomic comparisons. Great source book for a serious comp bio student.

DNA Microarrays: A Practical Approach
Edited by Mark Schena
Oxford University Press, Oxford, UK, 1999
A book on microarray technology. From DNA spotted on glass to enzymatic oligo arrays to ink jets, to microelectronic arrays. Written early on when many different approaches were being explored. Great source for technical information.

Mathematics of Genome Analysis
by Jerome K. Percus
Cambridge University Press; 1st edition 2002
Not a genomics book, but a mathmatician’ s look at DNA sequence, from clone libraries through seq alignments.

Post-genome Informatics
by Minoru Kanehisa
Oxford University Press, Oxford, 2000
Cool cover! Written by the guy behind KEGG. An eclectic choice of topics, first databases, then sequence analysis basics, then network analysis. Had a few pages on comparing networks that I found useful.

Guide to Analysis of DNA Microarray Data
by Steen Knudsen
John Wiley and Sons, New York, 2002
A what-to-do book on microarray data analysis. Very short, too short to explain how to do things, but describes what to do, issues to consider, and what results will look like. Useful as a place to start, will show you what you don’t know. The linked site has example R and BioConductor code.

Methods of Microarray Data Analysis II
Edited by Simon M. Lin and Kimberly F. Johnson
Springer, 2002
Papers from CAMDA ‘01 Various array analysis, especially advanced clsutering methods. Particularly interesting are:

• Biology-Driven Clustering of Microarray Data; K.R. Coombes, et al.
  GO-based clustering.
• Analysis of Gene Expression Profiles and Drug Activity Patterns by Clustering and Bayesian Network Learning; Jeong-Ho Chang, et al.
• Topomap and bayesian clustering

DNA Arrays: Technologies and Experimental Strategies
Edited by Elena V. Grigorenko
CRC Press, 2001
What caught my eye are the technology chapters, one on oligo arrays and another on electrochemical array detection.

DNA Arrays: Methods and Protocols
Edited by Jang B. Rampal
Humana Press, 2001
This is another array technology book. Great information on ink-jet and photolithographic oligo synthesis. There are several sequencing by hybridization articles. It starts with a chapter on the history of the field by Southern. Great book for a collection of articles!

Here’s a site with films of the tasmanian tiger, the thylacine (Thylacinus cynocephalus). It was driven to extinction in the 1930’s.

Thylacine films

There’s interest in sequencing the genome of the tasmanian devil with an eye toward eventual cloning. Reconstructing a genome of an extinct species is currently not technically feasible. So far they have been able to clone short DNA segments from preserved tissue.

I learn something new by way of David Appell

* For winds in mph (over 3 MPH) and Fahrenheit temperatures:
* Wind chill temperature = 35.74 + 0.6215T – 35.75V^0.16 + 0.4275TV^0.16

Formula from the National Weather Service.

How big a contributor to oil use are SUVs?

SUVs are about 1/4 of new cars sold, I can’t find figures for the total number of SUVs. People talk about SUVs because they have led the trend to lower fuel economy in US automobiles, and they are often brought up as a shorthand for talking about the fuel efficiency of US autos.

From googling a bit:
US autos account for 11% of world oil consumption, 8 million barrels per day.

SUVs, due to average lower fuel efficiency, take 33% more gas than cars. So let’s assume that SUVs are 15% of US autos. Then a switch to 5% SUVs in the US would save 0.3 million barrels per day, or 0.4% of world oil demand and 2% of US oil demand. So SUVs by themselves are fairly minor.

Increasing average fuel effciency of US autos by 5 MPG would save 1.3 million barrels per day, or reduce world oil demand by 1.8% and US oil demand by 6.5%.

So the fuel economy of US cars is a big deal.

Predicting future life expectancy is difficult. In a post, Kevin Drum of Politcal Animal at shows that the actuaries have done pretty well. He quotes one as saying that privately, they expected medical tech to provide faster gains in life span. I think they, and most others, expected a greater rise from medical advances. It has turned out that human biology is more complicated than anyone expected and that early successes with antibiotics and sterile technique were extraordinary. Since then it has been hard slogging.

The huge research effort into biology *will* pay off, but when? I expect it will pay off any time now (in a decade or two). Many different approaches to cancer treatment are being tried, I expect one will succeed. Heart disease can be fought both with biological approaches and with mechanical/electronics tech approaches

The other big factors are culture, business and the environment. US culture has become unhealthy, with people less active. I don’t expect that to change. The industrialization of food has been unhealthy. Effort has gone into making food tasty and cheap (sugary and fatty), and to use advertising to sell people more calories and bigger portions. My guess is that the food business will start pushing healthier food across the board. Healthy food will grow from the niche market it is now to become the norm.

The environment has had its ups (pollution controls) and downs (leaded gas, smog). I expect it will get worse, with overcrowding being the dominant factor. On the local side, I expect pollution will slowly get worse. On the global side, I expect that catastrophes will start popping up (oil scarcity, overfishing, lack of water, climate change, war, etc). Some will affect life in the US directly and others indirectly by slowing or reversing economic growth around the world.

How do all these factors integrate? I have no idea.

An planet around a star found by ESO is confirmed by the Hubble! This is the first confirmed image of an extra-solar planet. It’s a huge planet around a small star, but that’s the easiest sort of planet to see.

Article at space.com.

From an article on earthquakes following the tsunami in Asia a discussion of ways to trigger earthquakes!

Can earthquakes be tamed?
Human activity can cause quakes, but preventing them is harder
Cars are piled on top of each other in Phuket, Thailand in the tsunami’s aftermath
Barry West / EPA via Sipa Press
Can devastation such as that seen is this picture from Phuket, Thailand, be prevented?

Analysis
By James Oberg
NBC News space analyst
Special to MSNBC
Updated: 7:37 p.m. ET Dec. 27, 2004
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Accidental discoveries
People have triggered natural earthquakes through a number of activities on the Earth’s surface, most notably in the construction of large water reservoirs. As the weight of water accumulates in such reservoirs, lower rock layers yield to the stress and shift.

A different kind of large pit was behind what is probably the best-known epsiode of human-induced earthquakes. In 1961, the Army drilled a 12,000-foot disposal well at its Rocky Mountain Arsenal in Colorado, northeast of Denver. Beginning in March 1962, waste fluids from arsenal operations were dumped down the well.

Then a funny thing happened: An unusual series of earthquakes broke out in the area. By the end of 1962, there had been almost 200 earthquakes. At first they were small, but in December they damaged several buildings in nearby towns. Over the ensuing five years the quakes increased in frequency and force, and in April 1967 one measured magnitude 5.0.

A connection was soon established between the waste dumping and the earthquakes, and dumping stopped. The quakes continued, however. So the following year, the Army started to withdraw fluid from the well in an effort to reduce the quakes. Sure enough, as the fluid concentration in the deep rocks dropped, the quakes slowed down.

What was happening was that the fluids seemed to lubricate the rock layers that already were under tension. In that sense, the Army didn’t create the earthquakes, it just hurried them along by making it easier for the rocks to slip. Instead of one big quake at some point decades in the future, Colorado experienced a series of smaller quakes.

Could this principle be applied to other more famous fault lines? In theory, deep wells could insert fluids into one segment of a fault line, while other wells at the segment’s ends would suck out fluids thus releasing the tension harmlessly. The process could continue segment by segment as the fault line was tamed, forestalling a massive earthquake sometime in the future.

Daily cycling of the images in the left hand bar is now running!

It’s done with a perl script, cycle_web_images.

Old images go to the cavalcade page.

First post!

The install of WordPress went smoothly:

Unpack WordPress blogging software. Copy to /home/http/html/blog,
Copy wp-config-sample.php to wp-config.php and localize:

// ** MySQL settings ** //
define(’DB_NAME’, ‘wordpress’); // The name of the database
define(’DB_USER’, ‘jiml’); // Your MySQL username
define(’DB_PASSWORD’, xxxxx’’); // …and password
define(’DB_HOST’, ‘localhost’); // 99% chance you won’t need to change
this value

Run http://elegans.uky.edu/blog/wp-admin/install.php

It complains can’t see the DB, so do some hand setup:

MySQL setup:
mysql> create database wordpress;
grant all privileges on wordpress.* to jiml@localhost;
grant file on *.* to jiml@localhost;
grant select on wordpress.* to nobody@localhost;

Last two may be overkill, but can’t hurt.

OK, it tells me, “Now you can log in with the login “admin” and password
“b9cc0a”.”

Login, change password to . Start setup!