The International Society for Biocuration (ISB) Conference has put out a Call for Papers.  The deadline for abstracts is October 15, 2011.

The conference will take place April 2-4, 2012 in Washington, D.C.

For more information, please visit the ISB website.

In the August 19, 2011 issue, Nature News highlighted Science Exchange and featured an interview with the founder, Elizabeth Iorns. Science Exchange allows researchers to outsource their research to providers, other researchers or facilities that have the equipment to help the research get done. Read the entire interview at Nature News.

The goal of the AntibodyRegistry is to provide a stable, traceable, permanent identifier to all antibody products created by large commercial vendors and individual labs that can be included in any publication as a way to easily identify the antibody used in any scientific paper and trace that antibody back to the creator.

Within the Neuroscience Information Framework, the AntibodyRegistry provides results on antibody IDs, Antibody Name, Antibody Target, Target Species, Vendor, Clonality, Clone ID, Source Organism, Comments and Articles in which the particular antibody was used.  Whats more, the Antibody Registry is a deeply integrated, ‘virtual’ database pulling information from BioCompare, swant, the Journal of Comparative Neurology’s Antibody Database, Labome, NeuroMab and Novus within a single, unified results view.

Therefore, your search for a particular antibody no longer requires visiting multiple website (each with a slightly different lexicon) if you utilize the semantically enhanced search at NIF. For an example, check out the tutorial below.

Beginning from NIF’s homepage (neuinfo.org); we can search for “gene:pfdn2″. The search will return all the attributes mentioned above.

Clicking on the antibody ID will take you to the Antibody Registry website with more detailed information that looks like following.

Clicking on the Antibody name from the search result will take you to individual database that holds the information about the antibody.

For more detailed instructions on how to use Antibody Registry, please visit the tutorial.

The NIF Data Spotlight is a weekly blog post highlighting the databases, information, and resources curated by the Neuroscience Information Framework. For comments, questions or concerns feel free to drop us a line at curation@neuinfo.org.

It is likely that many of the members of SFN have read a bit of text when applying for NSF or NIH grants that states “thou shalt share thine data”. Actually the statements are here:

NSF Data Sharing Policy — According to NSF’s “Dissemination and Sharing of Research Results,” NSF says that “Proposals submitted or due on or after January 18, 2011, must include a supplementary document of no more than two pages labeled “Data Management Plan.” To get you started, please see below NIF’s “Data Management Plan” text template for NSF grants.

NIH Data Sharing Policy — According to NIH’s “Final NIH Statement on Sharing Research Data,” NIH’s policy is that “all investigator-initiated applications with direct costs greater than $500,000 in any single year will be expected to address data sharing in their application.”

So does this mean that SFN members are running to various databases to turn over all of their negative results? Are they clambering to post every file that their undergraduates produced to the World Wide Web? Have they accosted their university webmaster recently and loaded him/her with various disks? Well, not that we can see over in bioinformatics (see Nature special data issue).

So why would people want to share their data?

1. The scientific enterprise of various laboratories is paid for by the taxpayers and, as such, belongs to them. Yes, there is a lot of small print that needs to go at the end of this sentence having to do with timing of publication, human subjects etc., but the principle is sound.

2. The sharing of data is becoming possible, compared to a few years ago when my hard drive was a total size of 20MB. I think that this sort of storage space is now given away with each gumball purchase.

3. We all want to be immortal, and if the papers that we have published have not given us that immortality, perhaps our data will. In all reality, data are probably as important to the scientific enterprise as journal articles before 1975. We probably will not find any use for them in the next few years, but throwing them away should be rather distasteful.

4. Data, especially negative data, can be much more informative than ‘representative data’ as published in Figure 1. What I mean is that in a recent conversation with an NIH official, I discovered to my dismay that a clinical trial was recently aborted (aka tens of millions of dollars wasted) even though the preliminary animal data looked quite promising. The reason that was given was that most of the negative data was discarded into waste bins and not published. This is a very common practice, I have picked through stacks of data to find just the perfect “representative figure,” but this practice seems to be doing a disservice to science, and it may be time to change course.

5. Because we say so (here “we” means the informatics and computational neuroscientists)! While 1% of data may be published in some journal (which makes available an image file after you sign over your first-born to them), the rest of it could be used to find out some interesting answers that require aggregating data from many labs. There are lots of people that are computationally inclined (it may be contagious, don’t get too close to your grad students), and they need data. Actually, they need to have well-curated, meaningful data that they can use to feed their algorithms. The hope is that they will build interesting models that shed new light on brain function, but they can’t do it if you toss your intellectual output into the waste basket.

Why don’t people share?

1. It is difficult: While a data sharing plan is required, neither the NSF nor the NIH actually tells people how to share their data. Furthermore, there are projects and databases that can take certain kinds of data, but not others, and there are more than 1800 of these at our last count. Some journals also require submissions to certain databases before publishing, but not all do.

2. It is costly: In the case that a particular data can’t be found to have a home in a public database, then counting the cost of creating a database, systems support, a webmaster, proprietary tools etc., the cost can eat up the bulk of most RO1′s.

3. You get no credit! Scientists who share their data seem to be treated no differently than those that hoard their data. “Data sharers” receive no additional publications, no extra points toward their tenure review, although they do seem to be cited more often (PLOS article). Also, the NIH seems not to have any mechanism in place, at the moment, to check whether the data were indeed shared.

4. “It’s mine, my precious!!!” (the creature known as Gollum). Need I say more?

So here are some things that we in bioinformatics can do to help:

We bio-informaticians (aka those of us with databases) can all make an effort to structure database submission such that it is transparent, easy-to- reference in publications, and relatively fast. We need to make sure that the researcher is not burdened with a 400 item minimal information checklist and a deep ontological modeling of their data! Biologists mostly just need to submit an excel sheet with some numbers in it and some identifying information, i.e., if they tell you that their subject is a B6, then don’t ask if it’s a mouse!

We made a cheat-sheet! At the Neuroscience Information Framework (NIF), we have compiled a few of the data sharing statements and put them up on the web, so they can be shamelessly copied. Of course our motive is that we would like to get the data, at the time of publication as our algorithms and our continued support from NIH seems to depend on it.

We should also be able to make it easy to find a good database to submit data to. The NIF project was built to account for all the things that NIH funded in informatics (how many databases are there for RNAi? Answer), but has grown to include a deep search of more than 80 databases and has a catalog of over 3800 projects including software tools, atlases and core facilities. This means that we are in a good position to know which projects could take your data, and if none will, then we will put the data up as we already have the infrastructure and computer geeks required. Furthermore, we have some neuro-biologists that can help translate neuro-English to computer-geek-ease!

There are many other issues in data publishing, and I hope that this post will help to stimulate that discussion.

Cheers,

——————————————-
Anita Bandrowski
NIF Project Lead
UCSD
abandrowski@ucsd.edu
(858) 822-3629
——————————————-

Gene Expression Omnibus (GEO) is an another database of NCBI that holds gene expression information. It international public repository that archives and freely distributes microarray, next-generation sequencing, and other forms of high-throughput functional genomics data submitted by the research community. It provides robust and versatile database of gene expression profiles that provides an opportunity for scientists to easily submit their research and query for others’ works.

NIF’s federated search engine provides variety of information from GEO, including GEO Accession, experiment description, experiment type, organism, platform, technology and contributor. Any of these categories can be used to search related expression profiles in GEO. For example, if we wanted to look up some data on human’s snp variation. We can search for “human snp variation” and navigate to Data Type > Microarray > GEO:GEO, and browse for any gene expression profile of interest (shown below).

Clicking on the GEO accession number will direct the users to the more detailed page in GEO. The page will show you more detailed description of the experiment and its results. They also have downloadable files that users can download.

The NIF Data Spotlight is a weekly blog post highlighting the databases, information, and resources curated by the Neuroscience Information Framework. For comments, questions or concerns feel free to drop us a line at curation@neuinfo.org.

NIF Webinar – June 21st, 2011

“Ontology-based Analysis of Human Brain Activity; Recent work in the Development & Application of NEMO” was presented by Dr. Gwen Frishkoff, the Director of the NEMO consortium.

The goal of the NEMO project is to represent what we know about complex patterns in human event-related potentials. As discussed by Dr. Frishkoff, most neuroscientists and electrophysiologists can agree that there are 3 primary categories to analyze patterns in EEG and MEG data: Time, as the latency of peak positive or peak negative potentials, Space, as in scalp topography and function, the experimental context in which patterns are observed (i.e. presentation of visual stimulus).

The major problem in EEG and MEG data analysis, according to Dr. Fishkoff, is a lack of integration.  The NEMO project has a three tiered approach to this problem;

1) Develop a formal ontology for ERP domain concepts.
2) Create a suite of tools for automated-pattern extraction and ontology-based annotation for better data analysis.
3) Apply tools across datasets to prove applicability.

For more information, we invite you to view the full webinar here.

Last week, we had a look at PubMedHealth: Drug but this was just scratching the surface of this resourse. PubMedHealth holds a wide spectrum of  information to aid scientists in research. In this blog, we will explore PubMedHealth: Test, a portion of PubMedHealth that focuses on tests and treatments.

In NIF, you can find description of biomedical tests as well as information which will help understand test results. For example, if we wanted to learn more about PET scans, we search for it in the NIF with search syntax “PET scan”. The result returns test name, test description, title (which is a question regarding the test), and text (which is an answer to the question). The result also shows different kinds of PET scans (shown below).

You can click on the test that you are most interested in, and NIF will take you to the PubMedHealth website for more information.

The NIF Data Spotlight is a weekly blog post highlighting the databases, information, and resources curated by the Neuroscience Information Framework. For comments, questions or concerns feel free to drop us a line at curation@neuinfo.org.

This weeks featured NIFarious Idea is the Universe Sandbox, a game-like, yet educational interactive space simulator.

Available for download on Windows PCs only, the Universe Sandbox lets you “play god” with astrological bodies. Moreso physics-based than anything else, the Universe Sandbox begins with a brief walk-through to explain the basic controls: change a planets diameter, shift a moons orbit, hurl a star into Saturn, manipulate a comet’s velocity or trajectory – at let the fun unfold, nothing is off limits!

It also comes pre-programmed with several perspectives: Our Solar System, Our Local Galaxies, Earth & Moon, Saturn & Moon, Small Scale Gravity, Floating Moons, Collision with Jupiter, Nearby Stars, Uranus & Moons, Jupiter & Moons, Galaxy Collision, Neptune & Moons, Constellations and Planets & All Moons. For a better idea of the fun, check out the YouTube video here: Universe Sandbox – Interactive Space Simulator. A screenshot of “Our Solar System” is below.

Destroy planets, fly around Deep Space and learn about astrophysics all at the same time? Now thats dangerous…and for that, we thank you Universe Sandbox!

In previous blog post, we have looked at NCBI’s Entrez: Gene. This week we will be take a look at another component of NCBI, PubMedHealth: Drug. PubMed Health offers up-to-date information on diseases, conditions, drugs, treatment options, and healthy living, with a special focus on comparative effectiveness research from institutions around the world. We will be focusing on the drug portion and how it can be accessed through the NIF.

Drug title, questions regarding the drug and its answers can be searched through the NIF. For example, if you need more information on oxycodone, a strong pain reliever, try searching NIF for “oxycodone use”. PubMedHealth: Drug can be navigated by Data Type > Drugs > PubMedHealth: Drug (shown below).

The results will show the drug name, title (which is a question), and text (which is an answer to the question). Clicking the drug title will take you to the PubMed Health page with more detailed information about the drug.

The NIF Data Spotlight is a weekly blog post highlighting the databases, information, and resources curated by the Neuroscience Information Framework. For comments, questions or concerns feel free to drop us a line at curation@neuinfo.org.

Researcher’s at the University of Nottingham recently sent C. elegans, a popular animal model, into space on the Space Shuttle Atlantis. Why?

Well, to learn about how Space effects gene transcription of course! In particular, the functioning of RNA interference (RNAi).

One of the major problems with Deep Space travel is muscle atrophy. In zero gravity, astronauts suffer from dramatic muscle loss. To address this problem, the researchers used RNAi to block proteins (lysosomal cathespsins) necessary for muscle atrophy. As reported in “The Effectiveness of RNAi in Caenorhabditis elegans Is Maintained during Spaceflight“, the researchers confirmed that RNAi functions in space as it does on Earth and effectively prevented the degradation of muscle-specific α-actin proteins.

Not only is this good news for the prospects of Deep Space travel, but this research also provided the first evidence that RNAi can be utilized to prevent muscle protein degradation on Earth for pathologies in the sick and elderly!

Space-based scientific experimentation?! Now thats always a dangerous idea…and for that we thank you C. elegans!