Our lab's long-standing collaboration with the group of George Kollias at the Biomedical Sciences Research Center "Alexander Fleming" is bearing fresh fruit in our latest publication that came out last week at Arthritis and Rheumatology.
The paper titled "Genomic responses of mouse synovial fibroblasts during TNF-driven arthritogenesis greatly mimic those of human rheumatoid arthritis" is the result of a couple of years of efforts with colleagues and friends Evangelos Ntougkos and Panagiotis Chouvardas to analyze the arthritogenic potential of synovial fibroblasts in a transgenic mouse model of Rheumatoid Arthritis. It is a work that took a long (perhaps too long) time to come out and which is (in my view) not over yet as a number of questions remain to be answered from the copious amounts of data we have gathered. For those of you who are too bored or too busy to go through the paper beforehand you can take a look at its editorial commentary, in which Ulf Muller-Lander and Elena Neumann give a concise but short summary of our findings and close with a rather intriguing comment on our bioinformatics work saying that:
"Taken together, the paper shows nicely that the large scale puzzle RA cannot be solved by pouring millions of highly variable fragments into a high-end bioinformatics computer but only piece by piece by innovative scientists with careful evaluation of hypothesis-driven data sets."
I will be covering this last comment and a number of questions that are cracked open by our work in an upcoming post on our CG2 blog.
(For the time being I am off to grade some grad papers)
The paper titled "Genomic responses of mouse synovial fibroblasts during TNF-driven arthritogenesis greatly mimic those of human rheumatoid arthritis" is the result of a couple of years of efforts with colleagues and friends Evangelos Ntougkos and Panagiotis Chouvardas to analyze the arthritogenic potential of synovial fibroblasts in a transgenic mouse model of Rheumatoid Arthritis. It is a work that took a long (perhaps too long) time to come out and which is (in my view) not over yet as a number of questions remain to be answered from the copious amounts of data we have gathered. For those of you who are too bored or too busy to go through the paper beforehand you can take a look at its editorial commentary, in which Ulf Muller-Lander and Elena Neumann give a concise but short summary of our findings and close with a rather intriguing comment on our bioinformatics work saying that:
"Taken together, the paper shows nicely that the large scale puzzle RA cannot be solved by pouring millions of highly variable fragments into a high-end bioinformatics computer but only piece by piece by innovative scientists with careful evaluation of hypothesis-driven data sets."
I will be covering this last comment and a number of questions that are cracked open by our work in an upcoming post on our CG2 blog.
(For the time being I am off to grade some grad papers)
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