Machine learning methods for detecting structure in metabolic flow networks

Metabolic flow networks are large scale, mechanistic biological models with good predictive power. However, even when they provide good predictions, interpreting the meaning of their structure can be very difficult, especially for large networks which model entire organisms. This is an underaddressed problem in general, and the analytic techniques that exist currently are difficult to combine with experimental data. The central hypothesis of this thesis is that statistical analysis of large datasets of simulated metabolic fluxes is an effective way to gain insight into the structure of metabolic networks. These datasets can be either simulated or experimental, allowing insight on real world data while retaining the large sample sizes only easily possible via simulation. This work demonstrates that this approach can yield results in detecting structure in both a population of solutions and in the network itself. This work begins with a taxonomy of sampling methods over metabolic networks, before introducing three case studies, of different sampling strategies. Two of these case studies represent, to my knowledge, the largest datasets of their kind, at around half a million points each. This required the creation of custom software to achieve this in a reasonable time frame, and is necessary due to the high dimensionality of the sample space. Next, a number of techniques are described which operate on smaller datasets. These techniques, focused on pairwise comparison, show what can be achieved with these smaller datasets, and how in these cases, visualisation techniques are applicable which do not have simple analogues with larger datasets. In the next chapter, Similarity Network Fusion is used for the first time to cluster organisms across several levels of biological organisation, resulting in the detection of discrete, quantised biological states in the underlying datasets. This quantisation effect was maintained across both real biological data and Monte-Carlo simulated data, with related underlying biological correlates, implying that this behaviour stems from the network structure itself, rather than from the genetic or regulatory mechanisms that would normally be assumed. Finally, Hierarchical Block Matrices are used as a model of multi-level network structure, by clustering reactions using a variety of distance metrics: first standard network distance measures, then by Local Network Learning, a novel approach of measuring connection strength via the gain in predictive power of each node on its neighbourhood. The clusters uncovered using this approach are validated against pre-existing subsystem labels and found to outperform alternative techniques. Overall this thesis represents a significant new approach to metabolic network structure detection, as both a theoretical framework and as technological tools, which can readily be expanded to cover other classes of multilayer network, an under explored datatype across a wide variety of contexts. In addition to the new techniques for metabolic network structure detection introduced, this research has proved fruitful both in its use in applied biological research and in terms of the software developed, which is experiencing substantial usage.EPSR

Feasibility of Bedded Hoop Barns for Market Beef Cattle in Iowa: Cattle Performance, Bedding Use, and Environment

The objective was to document a bedded hoop barn for feeding market beef cattle. A comparison between a bedded hoop barn (15.2 × 36.6 m) and an open-front feedlot building (11.0 × 61.0 m) was conducted in southwest Iowa. The hoop barn was oriented north-south on a ridge with no windbreak. In summer, temperature was relatively consistent between the structures and ambient conditions, although the north end of the hoop barn had a slightly elevated dew point temperature. A summer temperature-humidity index showed that the hoop barn had fewer hours in alert category than either open front or ambient conditions. In winter, a cold stress index showed that the open-front barn provided the most shelter for the cattle with 92% of the hours classified as no impact, compared with the hoop barn at 77% and ambient at 51%. Both ends of the hoop barn were open, except for piled big round bales for a windbreak during winter. Growth, feed-to-gain, and dry matter intake for the cattle were similar between housing systems. Quality and yield grades were similar. Mud scores may be less for cattle from the bedded hoop barn compared with the open-front feedlot where mud was possible. Labor usage was similar for the hoop barn and the open-front feedlot. Labor occurred throughout the feeding period for the hoop barn because manure cleaning occurred weekly. Bedded hoop barns offer a viable alternative for feeding beef cattle and may reduce feedlot runoff

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Beef Cattle Feeding in a Deep Bedded Hoop Barn: A Preliminary Report

There is growing concern about more intensive runoff and environmental regulations for open beef cattle feedlots, particularly in the higher rainfall cattle feeding states like Iowa. A low-cost, versatile bedded hoop barn for feeding cattle may be a possible solution to this situation. The objective of this study is to quantify the environment in a bedded hoop used for finishing beef cattle and to compare beef cattle performance in hoops to conventional open feedlots. In order to compare bedded hoop barns to outside feedlots for beef cattle feeding, a hoop barn (50 x 120 ft) is being constructed at the ISU Armstrong Research Farm, Lewis, IA that will house 120 head of steers in three pens with approximately 50 square feet per animal. The hoop barn will have a fenceline feedbunk with concrete apron and scrape alley. The remaining floor will use crushed rock over geotextile fabric. Cornstalk bedding will be used to facilitate solid manure handling. Manure will be composted during the summer and winter months for land application in spring and fall. The hoop system will be compared with an outside feedlot with shed, under common management. Data will be collected and summarized on the following items: facility cost, feed intake, feed efficiency, cost of gain, daily gain, bedding use, manure output, and labor requirement. The project is being conducted in western Iowa, an area with many outside beef cattle feedlots. Design features and decisions included: a north-south orientation, 10 ft sidewalls, a fenceline bunk along the east edge of the hoop, a fabric covered overhang to shelter the fenceline bunk, three equal pens, a continuous open ridge vent, concrete paving along the bunks and for the scrape alley, and a curtain to close the west wall and north wall if needed. Results of this study will be ongoing, beginning in 2005

Beef Cattle Feeding in a Deep-Bedded Hoop Barn: Year Two

A three-year study evaluating the performance of yearling steers in a deep-bedded hoop barn has completed the second year. A 50 × 120 foot hoop barn was constructed at the ISU Armstrong Research Farm in the late fall of 2004. The comparison feedlot is an outside lot with shelter that includes a drive-through feed alley. Two groups of yearling steers were fed each year. The summer/fall groups were put on test in August and marketed in November. The winter/spring groups were put on test in December and marketed in two drafts in April/May. Overall the cattle performed similarly with similar carcass data for both housing systems. The information presented is for two years of a three-year study. The cattle had a lower mud score in the hoop barn, particularly for the winter/spring feeding periods. As expected the deep-bedded hoop system used more bedding than the semi-confinement lots. The bedded hoop barn required about 5 to 6 lb of cornstalk bedding per head per day that the steers were on feed

Beef Cattle Feeding in a Deep-Bedded Hoop Barn: Year One

A three-year study evaluating the performance of yearling steers in a deep-bedded hoop barn has completed the first year. A 50 × 120 foot hoop barn was constructed at the ISU Armstrong Research Farm in the late fall of 2004. The comparison feedlot is an outside lot with shelter that includes a drive-through feed alley. For the first year of the three-year study, two groups of yearling steers were fed. The first group (Group 1) was put on test August 5, 2005 and marketed on November 15, 2005 for a summer/fall feeding period. The second group (Group 2) was put on test December 21, 2005 and marketed in two drafts on April 4, 2006 and May 10, 2006 for a winter/spring feeding period. Overall the cattle performed similarly with similar carcass data for both housing systems. The information presented is the first year of a three-year study. The cattle had a lower mud score in the hoop barn, particularly for the winter/spring feeding period. As expected the deep-bedded hoop system used more bedding than the semi-confinement lots. The bedded hoop barn required about 5 to 6 lb of cornstalk bedding per head per day that the steers were on feed

Beef Cattle Feeding in a Deep Bedded Hoop Barn: A Preliminary Study

A deep bedded hoop confinement building was constructed at the ISU Armstrong Research Farm in Southwest Iowa in 2004. The building consists of three pens. Shortly after the completion of construction a preliminary study was initiated to compare performance, carcass characteristics, and bedding and labor use to that of a conventional semi-confinement system. The cattle used in this study were steer and heifer calves from the ISU McNay Research Farm. Performance and carcass measurements appeared similar comparing the two systems. However, the hoop building cattle used more bedding and appeared to have lower mud scores. Labor use may have favored the hoop building compared to the conventional system. In 2005, a three year study was initiated to compare the systems with yearling steers. Two turns of yearling cattle will be fed each year, one in summer and one in winter