Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText.
Kick-your-searchterm to multiple Engines kick-your-query now !>
A dictionary by aggregated review articles of nephrology, medicine and the life sciences
Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

suck abstract from ncbi


10.1097/MCP.0000000000000296

http://scihub22266oqcxt.onion/10.1097/MCP.0000000000000296
suck pdf from google scholar
C5084451!5084451!27468134
unlimited free pdf from europmc27468134    free
PDF from PMC    free
html from PMC    free

suck abstract from ncbi


Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\27468134.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117
pmid27468134      Curr+Opin+Pulm+Med 2016 ; 22 (5): 500-8
Nephropedia Template TP

gab.com Text

Twit Text FOAVip

Twit Text #

English Wikipedia


  • In Silico Modeling of Granulomatous Diseases #MMPMID27468134
  • Crouser ED
  • Curr Opin Pulm Med 2016[Sep]; 22 (5): 500-8 PMID27468134show ga
  • Purpose of the Review: The pathogenesis of genetically complex granulomatous diseases, such as sarcoidosis and latent tuberculosis, remain largely unknown. With the recent advent of more powerful research tools, such as genome-wide expression platforms, comes the challenge of making sense of the enormous data sets so generated. This manuscript will provide demonstrations of how in silico (computer) analysis of large research data sets can lead to novel discoveries in the field of granulomatous lung disease. Recent Findings: The application of in silico research tools has led to novel discoveries in the fields of non-infectious (e.g., sarcoidosis) and infectious granulomatous diseases. Computer models have identified novel disease mechanisms and can be used to perform ?virtual? experiments rapidly and at low cost compared to conventional laboratory techniques. Summary: Granulomatous lung diseases are extremely complex, involving dynamic interactions between multiple genes, cells and molecules. In silico interpretation of large data sets generated from new research platforms that are capable of comprehensively characterizing and quantifying pools of biological molecules promises to rapidly accelerate the rate of scientific discovery in the field of granulomatous lung disorders.
  • ä


  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    Linkout box