The Internet-accessible Profile Server at the SDSC has been an invaluable resource for my group's biocomputational research. Our ability to detect distant similarities between protein sequences is heightened considerably by the use of sensitive sequence profiles pioneered by Dr. Gribskov. The rationale is simple: the explosive growth of sequence databases-driven by varied genome projects-poses a great challenge to the biologist's repertoire of computational tools. It has become routine to plumb these databases for sequence homologs of cloned genes as a means to quickly assign structural or functional features to the new protein chain. However, most search algorithms are limited in their ability to efficiently cluster sequences that bear faint, fragmentary similarities to the probe chain; these relationships often provide the most valuable insights into the evolutionary design of a novel protein. We rely on the iterative buildup of sequence alignments -often aided by pattern-matching routines such as the NBCR's CAP and MOST programs-and the derivation of sequence profiles (and HMMs -Hidden Markov Models) to significantly extend the reach of database searches. My group's research delves into the structure and evolution of protein families that may be related by peculiar sequence motifs or three-dimensional folds, and participate in signaling pathways downstream of transmembrane receptors. Experimentally, we often seek homologs of our vertebrate signaling pathways in model organisms-nematodes, drosophila, yeast or even bacteria-and this often necessitates the identification of proteins that have significantly diverged in sequence-profiles are a powerful tool that ease this task. The SDSC Profile Server is uniquely configured to increase the sensitivity of profile searches by offering a 'weighting' feature that corrects for a skewed distribution of sequences in a multiple alignment file, and offers users the choice between two profile types ('Average' and 'Evolutionary'); the Server also provides a scan of the constructed profile against the latest Swissprot database release. The Server is very reliable, fast and widely accessible to researchers that have an Internet connection. Because of its ease of use and powerful applicability, I have found it an essential site to recommend to scientists, including new postdoctoral fellows or graduate students in my group or in neighboring labs at the Institute, as a tool that they should use.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR008605-05
Application #
6282934
Study Section
Project Start
1998-06-01
Project End
1999-04-14
Budget Start
Budget End
Support Year
5
Fiscal Year
1998
Total Cost
Indirect Cost
Name
University of California San Diego
Department
Type
DUNS #
077758407
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Pantoja, Joe Luis; Morgan, Ashley E; Grossi, Eugene A et al. (2017) Undersized Mitral Annuloplasty Increases Strain in the Proximal Lateral Left Ventricular Wall. Ann Thorac Surg 103:820-827
Morgan, Ashley E; Wozniak, Curtis J; Gulati, Sarthak et al. (2017) Association of Uneven MitraClip Application and Leaflet Stress in a Finite Element Model. JAMA Surg 152:111-114
Morgan, Ashley E; Pantoja, Joe L; Grossi, Eugene A et al. (2016) Neochord placement versus triangular resection in mitral valve repair: A finite element model. J Surg Res 206:98-105
Purvine, Emilie; Monson, Kyle; Jurrus, Elizabeth et al. (2016) Energy Minimization of Discrete Protein Titration State Models Using Graph Theory. J Phys Chem B 120:8354-60
Bucero, Marta Abril; Bajaj, Chandrajit; Mourrain, Bernard (2016) On the construction of general cubature formula by flat extensions. Linear Algebra Appl 502:104-125
Ebeida, Mohamed S; Rushdi, Ahmad A; Awad, Muhammad A et al. (2016) Disk Density Tuning of a Maximal Random Packing. Comput Graph Forum 35:259-269
Yang, Pei-Chi; Boras, Britton W; Jeng, Mao-Tsuen et al. (2016) A Computational Modeling and Simulation Approach to Investigate Mechanisms of Subcellular cAMP Compartmentation. PLoS Comput Biol 12:e1005005
Watson, Shana R; Liu, Piaomu; Peña, Edsel A et al. (2016) Comparison of Aortic Collagen Fiber Angle Distribution in Mouse Models of Atherosclerosis Using Second-Harmonic Generation (SHG) Microscopy. Microsc Microanal 22:55-62
Ge, Liang; Wu, Yife; Soleimani, Mehrdad et al. (2016) Moderate Ischemic Mitral Regurgitation After Posterolateral Myocardial Infarction in Sheep Alters Left Ventricular Shear but Not Normal Strain in the Infarct and Infarct Borderzone. Ann Thorac Surg 101:1691-9
Morgan, Ashley E; Pantoja, Joe Luis; Weinsaft, Jonathan et al. (2016) Finite Element Modeling of Mitral Valve Repair. J Biomech Eng 138:021009

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