This week’s BioGPS featured article is really interesting because it looks at PPARγ targets in DRG neurons vs adipocytes in hopes of understanding how lipid metabolism influences and is influenced by the peripheral nervous system. Check it out: BioGPS Featured Article – Evaluation of the Synuclein-γ (SNCG) Gene as a PPARγ Target in Murine Adipocytes, Dorsal Root Ganglia Somatosensory Neurons, and Human Adipose Tissue. | The Su Lab.
In silico molecular cytogenetics: bioinformatic approach to prioritization of candidate genes and copy number variations for basic and clinical genome research
via BioGPS Featured Article – In silico molecular cytogenetics: a bioinformatic approach to prioritization of candidate genes and copy number variations for basic and clinical genome research | The Su Lab.
Glioblastoma Multiforme is one of the most common and difficult to treat forms of brain cancer. Because it’s often aggressive and deadly, researchers (like the ones responsible for this week’s BioGPS featured article) have been working hard to uncover new therapeutic approaches for treating this disease. In this study, researchers employed proteomic profiling in conjunction with a technology termed >“bioorthogonal chemical reporter” (BOCR) strategy and LFQ-MS in order to analyze cell surface sialoglycoproteins in cells derived from GBM tumor patients.
Get the scoop on this week’s BioGPS featured article here
Here’s some quick background for this week’s BioGPS featured article. transcription factors play an important role in gene expression, but there’s still a lot to be learned with regards to how they actually work.
The authors of this paper chose to use mouse haematopoiesis as a model for learning more about how transcription factors work because the spacing between DNA binding motifs has been reported to be functionally important in mouse haematopoiesis.
Finally, checkout the tools the authors behind this paper have worked on: CODEX (formerly HAEMCODE)
Adverse effects are one of many reasons why drug development is so expensive, and one reason why this week’s BioGPS Featured article is so interesting.
The drug development process typically looks something like this:
Not only does it take a long time to develop a drug, the risk of failure is quite high and each failure is costly. According to a study last year in Nature Biotechnology, about 10% of all indication development paths make it through phase I clinical trials (looking at safety) successfully. Because of the small numbers in Phase I, it’s hard to determine if observed side effects are general or patient-specific.
This week’s featured article aims to use multi-omics to “estimate the systemic impact (side/adverse events) of (novel) therapeutic targets.” The researchers focus on rheumatoid arthritis which is a very complex disease and also accounts for 20% of the Top 10 clinical trial failures in 2013 as ranked by the size of the writedowns associated with the trial outcome.