TY - CHAP
T1 - Use of protein microarrays for molecular network analysis and signal- pathway profiling
AU - Calvo, Katherine R.
AU - Liotta, Lance A.
AU - Petricoin, Emanuel F.
N1 - Publisher Copyright:
© 2007 by Taylor & Francis Group, LLC.
PY - 2007/1/1
Y1 - 2007/1/1
N2 - Human disease is thought to be largely genetic in etiology. Underlying genetic mutations can be inherited through the germ line, or they can occur as the result of somatic mechanisms. Such mutated genes encode altered proteins that perturb normal cellular physiology, resulting in disease. The current ongoing revolution in molecular medicine has begun to elucidate the molecular basis of human disease, with the ultimate goal of developing rationally designed and targeted therapies. This process of investigation has consisted of multiple evolving and overlapping phases. The gene-discovery phase has been largely driven by key technological advances, including polymerase chain reaction (PCR), high-throughput sequencing, and the availability of low-cost computing, all of which have contributed to a revolution in bioinformatics. This phase culminated in the completion of the Human Genome Project in 2003 [1, 2], 50 years following the discovery of the DNA double-helix molecule. Now that the genome-sequencing effort is almost entirely completed, there are ongoing efforts to identify genetic polymorphisms (e.g., single nucleotide polymorphisms [SNPs]) that point to disease predisposition or to unique responses to therapy, such as idiosyncratic drug side effects [3].
AB - Human disease is thought to be largely genetic in etiology. Underlying genetic mutations can be inherited through the germ line, or they can occur as the result of somatic mechanisms. Such mutated genes encode altered proteins that perturb normal cellular physiology, resulting in disease. The current ongoing revolution in molecular medicine has begun to elucidate the molecular basis of human disease, with the ultimate goal of developing rationally designed and targeted therapies. This process of investigation has consisted of multiple evolving and overlapping phases. The gene-discovery phase has been largely driven by key technological advances, including polymerase chain reaction (PCR), high-throughput sequencing, and the availability of low-cost computing, all of which have contributed to a revolution in bioinformatics. This phase culminated in the completion of the Human Genome Project in 2003 [1, 2], 50 years following the discovery of the DNA double-helix molecule. Now that the genome-sequencing effort is almost entirely completed, there are ongoing efforts to identify genetic polymorphisms (e.g., single nucleotide polymorphisms [SNPs]) that point to disease predisposition or to unique responses to therapy, such as idiosyncratic drug side effects [3].
UR - http://www.scopus.com/inward/record.url?scp=85055558490&partnerID=8YFLogxK
U2 - 10.1201/9781420015683
DO - 10.1201/9781420015683
M3 - Chapter
AN - SCOPUS:85055558490
SN - 9781574444667
SP - 115
EP - 130
BT - Functional Informatics in Drug Discovery
PB - CRC Press
ER -