Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Sierra/SM theory manual.

Presented in this document are the theoretical aspects of capabilities contained in the Sierra/SM code. This manuscript serves as an ideal starting point for understanding the theoretical foundations of the code. For a comprehensive study of these capabilities, the reader is encouraged to explore the many references to scientific articles and textbooks contained in this manual. It is important to point out that some capabilities are still in development and may not be presented in this document. Further updates to this manuscript will be made as these capabilites come closer to production level

Sierra/SM theory manual.

Presented in this document are the theoretical aspects of capabilities contained in the Sierra/SM code. This manuscript serves as an ideal starting point for understanding the theoretical foundations of the code. For a comprehensive study of these capabilities, the reader is encouraged to explore the many references to scientific articles and textbooks contained in this manual. It is important to point out that some capabilities are still in development and may not be presented in this document. Further updates to this manuscript will be made as these capabilites come closer to production level

A Scalable Parallel Multigrid Solver for Three Dimensional Adaptive Mesh Structural Analysis

266 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.A parallel multigrid algorithm for solution of adaptive structural analysis meshes (ParMASA) is described. The user inputs a coarse mesh. The coarse mesh is successively solved, error estimated, and refined. The refinement simultaneously reduces discretization error and creates a hierarchy of meshes for use by the multigrid solver. The mesh may be refined in an arbitrarily irregular anisotropic manner. A block data structure is implemented to facilitate the parallelization of this complex refinement algorithm. For parallel runs an efficient algorithm must have balanced load in all algorithm steps. In addition communication must be minimized. A variety of procedures to optimize parallel performance by modifying the structure of multigrid cycle, smoothers, and communication patterns are discussed. Benefits of the advanced refinement and efficient parallelization are discussed. Good speedups to hundreds of processors are obtained on an SGI Origin 2000. ParMASA shows excellent performance a 256 processor SGI Origin 2000. ParMASA can perform all required IO, refinement, error estimation, and solution steps of an over 10 million degree-of-freedom system of equations in only 142 seconds.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

A Scalable Parallel Multigrid Solver for Three Dimensional Adaptive Mesh Structural Analysis

266 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.A parallel multigrid algorithm for solution of adaptive structural analysis meshes (ParMASA) is described. The user inputs a coarse mesh. The coarse mesh is successively solved, error estimated, and refined. The refinement simultaneously reduces discretization error and creates a hierarchy of meshes for use by the multigrid solver. The mesh may be refined in an arbitrarily irregular anisotropic manner. A block data structure is implemented to facilitate the parallelization of this complex refinement algorithm. For parallel runs an efficient algorithm must have balanced load in all algorithm steps. In addition communication must be minimized. A variety of procedures to optimize parallel performance by modifying the structure of multigrid cycle, smoothers, and communication patterns are discussed. Benefits of the advanced refinement and efficient parallelization are discussed. Good speedups to hundreds of processors are obtained on an SGI Origin 2000. ParMASA shows excellent performance a 256 processor SGI Origin 2000. ParMASA can perform all required IO, refinement, error estimation, and solution steps of an over 10 million degree-of-freedom system of equations in only 142 seconds.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Presto user<U+2019>s guide version 2.6.

Presto is a Lagrangian, three-dimensional explicit, transient dynamics code for the analysis of solids subjected to large, suddenly applied loads. Presto is designed for problems with large deformations, nonlinear material behavior, and contact. There is a versatile element library incorporating both continuum and structural elements. The code is designed for a parallel computing environment. This document describes the input for the code that gives users access to all of the current functionality in the code. Presto is built in an environment that allows it to be coupled with other engineering analysis codes. The input structure for the code, which uses a concept called scope, reflects the fact that Presto can be used in a coupled environment. This guide describes the scope concept and the input from the outermost to the innermost input scopes. Within a given scope, the descriptions of input commands are grouped based on code functionality. For example, all material input command lines are described in a section of the user's guide for all of the material models in the code