Today’s tip is on a new genotype/phenotype resource from the Swiss Institute of Bioinformatics, or SIB. I was already a fan of many SIB tools and resources, and was using one (ENZYME) when I found a notice about SwissVar. SwissVar is described as ‘a portal to Swiss-Prot diseases and variants.’ It includes information about genotype-phenotype relationships for each specific variant, manually annotated from literature. Manual annotation adds a level of quality and believability to this data. The SwissVar portal also contains various pre-computed information that may aid in determining the effect of the variant. Genotype-phenotype searches can begin with either Medical Subject Headings, or MeSH terms (Disease), gene or protein names (General characteristics) or variants (Functional/structural features). There are multiple ways to modify your searches, and results are clean tables of data including gene/protein accessions, names, links to MeSH definitions and links to variation reports.
If your research could benefit from high quality, manually curated genotype/phenotype information, I suggest you watch this tip, and then explore SwissVar according to your own interests.
Out at a recent training I was talking to a scientist about resources for protein modifications–specifically glycans. There are special challenges and complexities about studying these residues and I was trying to direct him to resources that might offer some information. And then just last week I got notice that GlycoSuite is back online. So I thought I would mention that today:
ExPASy GlycoSuiteDB is back online
By Christine Hoogland
The Swiss Institute of Bioinformatics is pleased to announce the re-launch of GlycoSuiteDB, a product of Tyrian Diagnostics Ltd (formerly Proteome Systems Ltd). Thanks to this collaboration the glycan database is available in open access on the ExPASy website.
GlycoSuiteDB is a curated and annotated glycan database. The current Release 8.0 contains 9436 entries, sourced from 864 references. The content of the database was transcribed as is but will expand again. Within the next months new data relative to bacterial sugars will be included. In the coming year the database will evolve through collaborative work with glycobiologists including Prof. N. Packer who initiated the GlycoSuiteDB project. The database is now available from a new URL, you are welcome to update your bookmarks and websites accordingly: http://glycosuitedb.expasy.org/
Do you have some favorite genes? Well, of course you do–you are probably a researcher who has in the past worked on some specific genes, or you are interested in groups of genes or genomic regions. Or maybe classes of genes. There is a new resource that provides you with a score of how well a given protein coding gene is annotated, and possibly therefore understood. The GCI, or Gene Characterization Index, can tell you. http://cisreg.ca/gci/
I love the idea of this project. The team wanted to look at the gene space and understand how well we knew the human genes. They looked at the growth of our knowledge over time, too–which provides an interesting view of our progress–as shown in this figure from their web site. And they wanted to identify the darkness–where don’t we know enough? Where are some great genes to examine that we can learn some really new things?
That’s the kind of project I wanted to do when I was still in academia. I thought you could build a whole lab and crank out students who get assigned an unknown gene, and it is their job over the next few years to analyze and understand the gene. It would be unbiased by a disease area vision, or by the lab director’s preconceptions of what the gene might do. They could try all sorts of techniques to get there. It is probably also entirely unfundable by grant agencies. Alas.