Posts Tagged Biology

The great ideas of biology

The guardian has a series called “It’s a small world“, among which is a video called “Gregor Mendel and the genesis of genetics” where

Nobel laureate Sir Paul Nurse tells the story of another great idea in biology – genes as the basis of heredity – in a lecture at the Royal Institution in London. It all started with the gardening monk Gregor Mendel and his peas in the 19th century and reached a key milestone with the unravelling of the molecule of heredity, the DNA double helix, by James Watson and Francis Crick in 1953

The great ideas of biology covered are

  • the cell
  • the gene
  • natural selection
  • Life as chemistry
  • Biology as an organized system.

Similarly to “A Brief Introduction to GeneticsDavid Murawsky (as mentioned around here before, but hey, they repeat stuff on TV all the time, and not only the goodies) put another impressive clip out there: “18 Things You Should Know About Genetics“. Enjoy!

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The Federation of American Scientists (FAS) Learning Technologies Program (pre-)launched the Science Game Centerto demonstrate to teachers, scientists, museums, and parents the myriad ways games can be used to improve education in math and science“. Next to Phylo and Fold.it (which I mentioned around here before) are several entries listed I haven’t seen yet. It may be due to the movie “Fantastic Voyage” that made a lasting impression on me as a kid that “Immune attack” immediately caught my attention. After all, I’d rather kick some pathogenic butt than blowing up poor aliens in space. Good hunting!

P.S.: Reminds me of this quote by 137th Gebirg on battlestarforum.com

“I may appear unoccupied to you, but at the molecular level, I’m really quite busy.”

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Free Ivy-League Education

 After I mentioned theScienceNetwork in the previous post and you might already be aware of sites such as SciVee.tv, labtube.tv and iTunes U it’s time to share some recent links in the area of online-courses:

First, with a biological focus, there is iBioSeminars accompanied by iBioMagazine – let me just highlight this talk by David Baltimore.

On the computational side, there is udacity which was started by former Stanford professor and Google fellow Sebastian Thrun. He developed a vision for “University 2.0” under the motto of “democratizing higher education”. After having experienced that he could reach out to more people in a better way by a single online course than he could have by traditional teaching (even in huuuge overcrowded lecture halls) during the next couple of years he just couldn’t go back to the olden ways. He really has a point in dumping his professorship I heartily agree with, and that’s an understatement. I highly recommend to check out his talk at DLD (hosted by the gorgeous Maria Furtwängler), here is a teaser-trailer for the CS101-class “Building a Search Engine”:

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(You might want to check out this previous post on the online courses at Stanford)


To round things up, at the moment there is a free introductory course on Machine Learning “Learning from Data” ongoing at Caltech by Professor Yaser Abu-Mostafa covering basic theory, algorithms, and applications. Registration is still possible, the previous lectures are available here.

Video et studio, ergo sum.

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Visualizing Biological Data

The VizBi-2012 Conference took place in Heidelberg this week – unfortunately I couldn’t attend it. Nevertheless, I received a bit of summary and feedback: The talks will be made available online, I am looking forward to check out a few of them (i.e. Jim Robinson, Jernej Ule). Ivet Bahar (ProDy) and Valerie Daggett (Dynameomics) gave an interesting overview on Molecular Dynamics.

The conference was preceeded by a several tutorials on Monday. Among them on was one on Processing.js (which has been mentioned around here a few times before) and one on D3.js. Both are based on JavaScript and generate cool Visualisations for the Web. D3 only recently got onto my radar, it’s document driven approach seems quite powerful. So it’s definitely worth a look –

see some more examples (like the force-directed layout on the right) on http://mbostock.github.com/d3/ and the workshop slides can be found at http://bost.ocks.org/mike/d3/workshop/.

Thanks to to Corinna Vehlow for feedback!

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Goodbye to hairballs?

You probably have seen the hairballs resulting from a force-directed layout of complex biological networks. What do they tell you? Well, that the networks are rather complex. But for much more detailed analysis the classical visualizations are actually quite useless. The hiveplot  is an attempt to provide

“A scalable, computationally fast, and straight-forward network visualization method that makes possible visual interpretation of network structure and evolution.”

A laudable goal, if it works in practice for you and your data – check it out. In addition there is an R package available for creating hive plots in 2D and 3D called HiveR.

Also see Krzywinski M, Birol I, Jones S, Marra M (2011). Hive Plots — Rational Approach to Visualizing Networks. Briefings in Bioinformatics (doi: 10.1093/bib/bbr069).

Thanks to Lucy Colwell for the hint!

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Computer-to-Gene Interface

Using a light-activated gene-system, researchers from the ETH Zurich and UCSF demonstrated that gene-expression can be controlled from the outside using a computer.

The approach is a comparatively simple means to take control of fantastically complex biochemical processes to achieve a desired result.

see the report in the BBC Science & environment section “‘Cyborg’ yeast genes run by computer” – Unfortunately the original article in Nature Biotechnology (doi:10.1038/nbt.2018, 2011 advance online publication) is not OpenAccess:

In silico feedback for in vivo regulation of a gene expression circuit” (Andreas Milias-Argeitis et al.)

Probably belongs into the not-yet-existing category “Convergence of Life- and Information-Science”.

Shared via LinkedIn by Gary Johnson in Computational Biology

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Free Science Books

A collection of free science books is available (in .pdf format) at INTECHopen – among them are the following ones on experimental / computational aspects of systems biology and on HMMs which might be of interest:



(thanks to Zana Kadric for sharing via the group “Systems Biology” at LinkedIn)

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