Congratulations on an exciting new site, it looks like it's beginning to really shape up!
I figured maybe I can liven it up a bit with a small (beta) debut here. Maybe you'd like to have a look at my new (totally rewritten) software for bioinformatics analysis; it supports analyzing almost every type of file through some advanced information theory techniques. Try it and see, it's easy to use:
As discussed in a previous post, there is a sorry lack of open source LIMS (Laboratory Information Management System) software available.
I'm going to take the plunge and release a very alpha package to the world, called MamboLIMS. MamboLIMS is a LIMS package built using the Mambo Server CMS and 2 Mambo components - Peter Koch's fantastic Facile Forms package and DocMan for Mambo. The package contains 19 forms for managing many aspects of a biological research lab including a chemical inventory, fridge/freezer boxes, plasmids, microbial strains, oligos and book/equipment loans.
If you want to know more and try it out, read on.
I have just read an interesting article which discusses about the application of object-orientation paradigm, used in popular programming languages such as Ruby, Java or C#, in dynamical and statical description of different gene products and their derived forms. Object attributes and properties, which could refer to proteins and their ulterior complexes, come from vocabulary terms created in Gene Ontology initiative.
This is a very suggestion approximation, since it can unite the different ontologies and organization principles of GO (Molecular Function, Biological Process and Cellular Component) in the object context.
This enable, for instance, to use class diagrams generated with UML, in order to describe and simulate biological processes, and particularly, the interaction of their components.
I reproduce from the paper the correspondence between object-orientation principles and the integration of the model with Gene Ontology.
I have recently been put in charge of managing our department's -80°C cryostorage (ah the duties of a new PhD student...). Organization is chaotic: people come and go; they add new and forget old samples in the freezers... knowing what belongs to whom and whether or not we can toss it out can be impossible.
To ease department-wide, laboratory-wide and individual organization and tracking, we need a web-based system. Flexibility is the key word: some samples may be 1.5mL tubes of RNA hidden away in boxes and towers, and others may be whole birds or frogs. A superuser should be allowed to attribute space, while "simple" users should have complete control over their own space.
More work from Miguel Nicolelis' lab shows that the concept of self is very plastic. They show the brain adapts by plastically dedicating some "brain structure" for the control of the robot arm.
He talked about this in his seminar in one of my phd courses. It does resonate well with our intuitive feeling about tools. If we move to a different keyboard, and it has a different layout we will be severely slowed down. People that drive a car most likely will describe the experience of driving like the car is somewhat an extension of self. They will probably look at the mirrors without noticing they are doing so, etc.
Via hublog: "NCBI's PubMed is to offer RSS feeds for searches. Only took them 2½ years."
Update: Pubmed RSS is now live. After doing a Pubmed search, click on the drop down menu for "send to" and RSS is now one of the options. The feature allows you to specify a name for the feed and number of items to include, see here for an example of the result. Pubmed is using RSS version 2.0 and dumping the content of the HTML citation display directly into the description tag. For most users this won't matter as the display in most aggregators, like bloglines for example (see the bioinformatics folder), will be the same as the regular Pubmed site. However using RSS 1.0 with available modules would have enabled more metadata to be added to the feeds, see for example the semantically rich feeds produced by Connotea. Which is great if you're a Semantic Web fan, which we all are right ?
Interestingly it looks like RSS export is going to be part of the Eutils web services (see the feed url). Now if RSS 1.0 export was available from all the NCBI databases then we would have instant RDF data.
I'll leave commenting on issues such as the correct identifiers to use in the Pubmed RSS (lsids ?) and whether or not the RSS 2.0 feeds are valid, use best practices (entity encoding the HTML in the description elements) etc. for later as I'm busy with ISMB related activities.
Firefox, the latest offering from the Mozilla Foundation is one of the best web browsers in the market at the moment. In addition to built-in extras like popup-blocking, tabbed browsing, smart searching capabilities, the mozilla development platform offers more than 200 add-ons in the form of extensions.
According to the mozilla update site, the official download home for all extensions:
Extensions are small add-ons that add new functionality to your Mozilla program. They can add anything from a toolbar button to a completely new feature.
Firefox offers the average biologist many advantages over Internet Explorer or Opera.
I assume that frequent readers of nodalpoint have given talks at scientific meetings (otherwise known as conferences), in which case this excellent post entitled A field guide to biomedical meeting creatures, part 1: Any questions? will be familiar:
In any case, in observing a number of talks and in giving my own, it occurred to me that a little-appreciated art is that of dealing with people who will inevitably ask questions after you're done with your talk. It's a tough thing, as the people who come up to the microphone to ask questions sometimes have agendas that aren't always immediately apparent, agendas that often don't include simple curiosity about your results.
Because we all need a laught every now and then. If microsoft built cars.... Via Keats' telescope.
Ok, so with a slight time lag, here are my contributions. Rather predictably, they revolve around microarrays. Specifically, about the much vaunted power of microarrays when applied to molecular medicine, with particular reference to cancer profiling.
Michiels et al (Lancet editorial by Ioannides, Nature news story) reanalyse data from seven large cancer expression profiling studies, and conclude that, overall, predictive gene sets do not replicate across data sets.
