E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, February 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, March 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, April 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, May 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

Suicide after successful deep brain stimulation for movement disorders.

The authors observed a high rate of suicide (6/140 patients, 4.3%) in a large cohort of patients with movement disorders treated with deep brain stimulation (DBS). Apparent risk factors included a previous history of severe depression and multiple successive DBS surgeries, whereas there was no relationship with the underlying condition, DBS target, electrical parameters, or modifications of treatment. Paradoxically, all patients experienced an excellent motor outcome following the procedure. The authors propose that patients at high risk for suicide should be excluded from DBS surgery.

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, June 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, July 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

E-1 Monthly Statistical Movement Summary for Entire Iowa Department of Corrections, August 2004

Monthly Statistical Movement Summary for Entire Iowa Department of Corrections

E-1 MONTHLY STATISTICAL MOVEMENT SUMMARY FOR ENTIRE IOWA DEPT. OF CORRECTIONS September 2004

MONTHLY STATISTICAL MOVEMENT SUMMARY FOR ENTIRE IOWA DEPT. OF CORRECTIONS

An assessment of gene prediction accuracy in large DNA sequences

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

Islands of euchromatin-like sequence and expressed polymorphic sequences within the short arm of human chromosome 21

The goals of the human genome project did not include sequencing of the heterochromatic regions. We describe here an initial sequence of 1.1 Mb of the short arm of human chromosome 21 (HSA21p), estimated to be 10% of 21p. This region contains extensive euchromatic-like sequence and includes on average one transcript every 100 kb. These transcripts show multiple inter- and intrachromosomal copies, and extensive copy number and sequence variability. The sequencing of the "heterochromatic" regions of the human genome is likely to reveal many additional functional elements and provide important evolutionary information.

A comparison of random sequence reads versus 16S rDNA sequences for estimating the biodiversity of a metagenomic library

The construction of metagenomic libraries has permitted the study of microorganisms resistant to isolation and the analysis of 16S rDNA sequences has been used for over two decades to examine bacterial biodiversity. Here, we show that the analysis of random sequence reads (RSRs) instead of 16S is a suitable shortcut to estimate the biodiversity of a bacterial community from metagenomic libraries. We generated 10,010 RSRs from a metagenomic library of microorganisms found in human faecal samples. Then searched them using the program BLASTN against a prokaryotic sequence database to assign a taxon to each RSR. The results were compared with those obtained by screening and analysing the clones containing 16S rDNA sequences in the whole library. We found that the biodiversity observed by RSR analysis is consistent with that obtained by 16S rDNA. We also show that RSRs are suitable to compare the biodiversity between different metagenomic libraries. RSRs can thus provide a good estimate of the biodiversity of a metagenomic library and, as an alternative to 16S, this approach is both faster and cheaper.

Identifying protein-coding genes in genomic sequences

The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.

The mitochondrial targeting function of randomly generated peptide sequences correlates with predicted helical amphiphilicity.

A pool of oligonucleotides encoding a start methionine and nine random amino acids was inserted at the 5'-end of the gene for the yeast cytochrome oxidase subunit IV lacking its own mitochondrial targeting sequence. Approximately one-quarter of the randomly generated sequences targeted subunit IV to its correct intramitochondrial location in vivo. Sequence analysis of 89 randomly generated sequences showed that their efficiencies as mitochondrial targeting signals correlated with the potential to fold into an amphiphilic alpha-helix. Functional targeting sequences were enriched in arginine and isoleucine residues but contained few aspartate, glutamate, and proline residues. Nonfunctional sequences predicted to have significant helical amphiphilicity often had at least one acidic or multiple helix-breaking residues that would be expected to interfere with targeting functioning. These results support the hypothesis that the signal for targeting a protein into the mitochondrial matrix is usually a positively charged amphiphilic helix.