Data management and analysis for high-throughput DNA sequencingprojects

The rapid advances in molecular biology have begun to shift many of the bottlenecks in genome research from the laboratory to the data analysis facility. The pace at which this has occurred creates a situation in which software development always has to catch up with the flow of data. Since such large-scale processes were not anticipated, the analysis infrastructure has not been fully established. Furthermore, most systems that have been built were designed by the biologists who collected the data. More recently, computer scientists, mathematicians, and engineers have taken an interest in this problem. This has had a positive effect, since it has created a tight synergy between the informatics and the biology. Several principles affected the design of the system developed at TIGR. Each of the sample preparation, sequencing, and analysis steps had to be managed, scheduled, and tracked. This information had to be made readily available to those who needed it for carrying out their tasks. Different skill levels of the users had to be taken into account. The degree of human intervention at each step had to be evaluated and built into the design. A mixed processing environment of Macintosh and Unix platforms had to be integrated. Most importantly, the system had to save time, reduce error, and ensure uniformity of the analysis and quality of the results. In the authors' experience, the tools they have built work well because of their early decisions as to which systems to use for development. The authors settled on a robust relational database management system (Sybase) and a portable development environment (C, C++)     

Phosphorus Inputs to Lake Simcoe from 1990 to 2003: Declines in Tributary Loads and Observations on Lake Water Quality

Total phosphorus (TP) inputs to Lake Simcoe have led to hypolimnetic dissolved oxygen (DO) depletion and loss of cold water fish habitat. Since 1990, efforts have been made to reduce the total TP input to the lake below a defined target of 75 t/year, which was predicted to lead to reductions in spring TP concentration and improvements in end-of-summer hypolimnetic DO concentrations. The total TP load to the lake during the most recent period of record (1998/99-2003/04) ranged from 53 to 76 t/yr and averaged 67 t/yr, compared to an average of 114 t/yr estimated between 1990/91 and 1997/98 (range 85-157 t/yr). Reductions in TP loads from the catchment via tributary discharge (∼26 t) accounted for the majority of the decrease in total load between the two time periods. Total P concentrations decreased significantly in four out of six long-term monitored tributaries; however, concentrations in all six tributaries remain above the level recommended to avoid nuisance plant growth (30 μg/L). Although TP loads to the lake are currently below the target 75 t/yr, excessive growths of filamentous algae and macrophytes continue to be a problem in the nearshore zone. End-of-summer minimum hypolimnetic DO concentrations (average 4.3 mg/L, 1998/99-2003/04) remain substantially below the level (7 mg/L) that is considered protective of lake trout. Efforts to reduce TP loads to the lake therefore need to continue.     

Performance of a non‐load‐bearing steel stud gypsum board wall assembly: Experiments and modelling

A gypsum wall assembly was exposed to an intense real‐scale compartment fire. For the wall assembly, temperatures were measured at the exposed face, within the stud cavity, and at the unexposed face during the fire exposure. Total heat flux gauges were used to measure the temporal variation of the energy incident on the walls, and cameras, both visual and infrared, were used to image the unexposed face of the wall assembly during the fire exposure. The behaviour of the wall assembly under the fire load is discussed as are current model results for a simulation of the fire test. Copyright © 2006 John Wiley & Sons, Ltd.     

The design of experiments when there are errors in all the variables

The Error-in-Variables Model (EVM) applies to a large class of problems in parameter estimation in which there is error in all the variables. This property makes it of more general applicability than the widely used technique of ordinary Least Squares. While there is a voluminous literature on EVM there is nothing on a general method for designing experiments when EVM applies. In this paper we present an extension of the concept of D-optimality to provide such a general method. It is illustrated by applying it to the estimation of copolymer reactivity ratios and to fitting an ellipse.     

Automatic labeling and characterization of objects using artificial neural networks

Existing NASA supported scientific databases are usually developed and managed by a team of database administrators whose main concern is the efficiency of the databases in terms of normalization and data search constructs. The populating of the database is usually done in a manual fashion by row and column as the data become available, and the data dictionary is usually defined by the same team (at times with little input from the end science user). This process is tedious, error prone and self-limiting in terms of what can be described in a relational Data Base Management System (DBMS). The next generation Earth remote sensing platforms [i.e., Earth Observing System (EOS)] will be capable of generating data at a rate of over 300 Megabits per second from a suite of instruments designed for different applications. What is needed is an innovative approach that creates object-oriented data-bases that segment, characterize, and catalog, and are manageable in a domain-specific context, and whose contents are available interactively and in near-real-time to the user community. This paper describes work in progress that utilizes an artificial neural net approach to characterize satellite imagery of undefined objects into high-level data objects. The characterized data is then dynamically allocated to an object-oriented database where it can be reviewed and accessed by a user. The definition, development, and evolution of the overall data system model are steps in the creation of an application-driven knowledge-based scientific information system.     

Egg Thiamine Status of Lake Ontario Salmonines 1995–2004 with Emphasis on Lake Trout

Alewives (Alosa pseudoharengus), the major prey fish for Lake Ontario, contain thiaminase. They are associated with development of a thiamine deficiency in salmonines which greatly increases the potential for developing an early mortality syndrome (EMS). To assess the possible effects of thiamine deficiency on salmonine reproduction we measured egg thiamine concentrations for five species of Lake Ontario salmonines. From this we estimated the proportion of families susceptible to EMS based on whether they were below the ED20, the egg thiamine concentration associated with 20% mortality due to EMS. The ED20s were 1.52, 2.63, and 2.99 nmol/g egg for Chinook salmon (Oncorhynchus tshawytscha), lake trout (Salvelinus namaycush), and coho salmon (Oncorhynchus kisutch), respectively. Based on the proportion of fish having egg thiamine concentrations falling below the ED20, the risk of developing EMS in Lake Ontario was highest for lake trout, followed by coho (O. kisutch), and Chinook salmon, with the least risk for rainbow trout (O. mykiss). For lake trout from western Lake Ontario, mean egg thiamine concentration showed significant annual variability during 1994 to 2003, when the proportion of lake trout at risk of developing EMS based on ED20 ranged between 77 and 100%. Variation in the annual mean egg thiamine concentration for western Lake Ontario lake trout was positively related (p < 0.001, r² = 0.94) with indices of annual adult alewife biomass. While suggesting the possible involvement of density-dependent changes in alewives, the changes are small relative to egg thiamine concentrations when alewife are not part of the diet and are of insufficient magnitude to allow for natural reproduction by lake trout.