105,428 research outputs found
Large litters and low losses - a successful breeding goal in piglet production?
No full textFor this analysis individual birth weights of 13'019 piglets of BHZP-line 01 and 13'794 piglets of line 03 were available within two years. Genetic parameters were estimated for individual birth weight with random effects of animal, sow and litter. Litter size, mean birth weight and standard deviation of birth weight were estimated as a trait of the sow. Estimated heritabilities of individual birth weight were h(2)=.098 for line 01 and h(2)=.147 for Line 03. Heritabilities for litter size, mean birth weight and standard deviation of birth weight were estimated with. 119,.354 und .104 in Line 01 and .114, .276 und .130 in Line 03. Genetic correlations in Line 01 und Line 03 between litter size and mean birth weight were -.254 und -.661, between litter size and standard deviation of birth weights .563 und .280. Selection only on litter size reduces mean birth weight and increases the standard deviation of birth weights. In a further step two different selection strategies in combination with three different breeding goals were compared in a selection index. It could be shown, that a combination of litter size and mean birth weight causes a high genetic gain in the trait number of piglets weaned by increasing the number of piglets born alive and low (or none) increase of lost piglets. A high economic gain per generation can be reached, without increasing the number of piglet died before weaning
Large litters and low losses - a successful breeding goal in piglet production?
No full textFor this analysis individual birth weights of 13'019 piglets of BHZP-line 01 and 13'794 piglets of line 03 were available within two years. Genetic parameters were estimated for individual birth weight with random effects of animal, sow and litter. Litter size, mean birth weight and standard deviation of birth weight were estimated as a trait of the sow. Estimated heritabilities of individual birth weight were h(2)=.098 for line 01 and h(2)=.147 for Line 03. Heritabilities for litter size, mean birth weight and standard deviation of birth weight were estimated with. 119,.354 und .104 in Line 01 and .114, .276 und .130 in Line 03. Genetic correlations in Line 01 und Line 03 between litter size and mean birth weight were -.254 und -.661, between litter size and standard deviation of birth weights .563 und .280. Selection only on litter size reduces mean birth weight and increases the standard deviation of birth weights. In a further step two different selection strategies in combination with three different breeding goals were compared in a selection index. It could be shown, that a combination of litter size and mean birth weight causes a high genetic gain in the trait number of piglets weaned by increasing the number of piglets born alive and low (or none) increase of lost piglets. A high economic gain per generation can be reached, without increasing the number of piglet died before weaning
Variance and covariance estimates for litter size of purebred and crossbred sows
No full textThe aim of this study was the estimation of additive genetic variances and heritabilities of purebred and crossbred sows for the trait number of piglets born alive as well as the estimation of the genetic correlation between the litter size of purebred and crossbred sows. Two data sets were available for the analysis, which were very different in their genetic and organisational structure. At the one hand there was a data set from an Australian 3-way-crossbreeding program with litter performances of 8334 Large White sows (LW), 3262 Landrace sows (LR), 10416 LW LR crossbred sows and 1733 LR LW crossbred sows. For the genetic analysis no differences were made between the two reciprocal crosses. The data sets were recorded from October 1991 until November 1994 and were produced on the same farm, which was seperated in different breeding compartments (modules). On the other hand there was a second data set from the German Bundeshybridzuchtprogramm (BHZP). Litter preformances from 211006 purebred sows (01-sows) and 26422 crossbred sows (31-sows) were available. After the pedigree was set up the data set was reduced to 57263 purebred sows and 7773 crossbred sows. The data sets were recorded from the second quarter 1991 until third quarter 1996. The litter performances of the purebred sows were recorded on 181 different farms, the litter performances of the crossbred sows on 61 different farms. The results for the Australian data set showed heritabilities for number of piglets born alive in first, second and third litters of .059, .082 and .072 for Large White, .117, .158 and .063 for Landrace and .078, .083 and .090 crossbred sows. The genetic correlations between the litter size in first and second, first and third and second and third litter were for Large White .61, .51 and .99, for Landrace .77, .88 and .88 and for crossbred sows .88, .62 and .81, respectively. The estimated heritabilities for the German data set in first, second and third litters were .070, .069 and .099 for purebred and .077, .041 and .083 for crossbred sows. The genetic correlations between the litter size in first and second, first and third and second and third litter were for purebred sows .808, .700 and .957 and for crossbred sows .665, .576 and .98, respectively. Estimated coefficients of genetic correlations between purebred and crossbred performance were in the Australian data set .99, .69 and .83 (litter 1-3) and in the German data set .80, .99 and .81 (litter 1-3), respectively. The estimated correlations of the two very different structured data sets are very high, but they are only different in the second litter and confirm each other
ONDEX - a data integration framework for the life sciences
No full textTaubert J. ONDEX - a data integration framework for the life sciences. Bielefeld (Germany): Bielefeld University; 2011.Over the last decade biological research has changed completely. The reductionism approach of studying only a few biological entities at a time in the past is being replaced by the study of the biological system as a whole today. Systems Biology seeks to understand how complex biological systems work by looking at all parts of biological systems, how they interact with each other and form the complete whole. This process requires that existing biological knowledge (data) is made available to support on the one hand the analysis of experimental results and on the other hand the construction and enrichment of models for Systems Biology.
Effective integration of biological knowledge from databases scattered around the internet and other information resources (for example experimental data) is recognized as a pre-requisite for many aspects of Systems Biology research. However, systems for the integration of biological knowledge have to overcome several challenges. For example, biological data sources may contain similar or overlapping coverage and the user of such systems is faced with the challenge of generating a consensus data set or selecting the "best" data source. Furthermore, there are many technical challenges to data integration, like different access methods to databases, different data formats, different naming conventions and erroneous or missing data.
To address these challenges and enable effective integration of biological knowledge in support of Systems Biology research, the ONDEX system which is presented in this thesis was created. The ONDEX system provides an integrated view across biological data sources with the aim to enable the user to gain a better understanding of biology from integrated knowledge. ONDEX is supported by BBSRC (http://www.bbsrc.ac.uk/) as part of the System Approaches to Biological Research initiative (SABR) and is now mainly being developed at Rothamsted Research, Manchester University and Newcastle University. The first ONDEX prototype was developed at University of Bielefeld.
ONDEX uses a three steps approach to address the outlined challenges, namely import of data from data sources, identifying overlapping or similar data across different data sources and analysis of the resulting integrated datasets to reveal new biological insights. This thesis presents the most interesting aspects of the ONDEX system in more detail; all other parts of the ONDEX system will only be briefly described when appropriate
A broadly tuned network for affective body language in the macaque brain.
No full textData and visual stimuli from the publication: *Taubert, J., Japee, S., Patterson, A., Wild, H., Goyal, S., Yu, D., Ungerleider, L. G. (accepted) A broadly tuned network for affective body language in the macaque brain
A broadly tuned network for affective body language in the macaque brain.
No full textData and visual stimuli from the publication: *Taubert, J., Japee, S., Patterson, A., Wild, H., Goyal, S., Yu, D., Ungerleider, L. G. (accepted) A broadly tuned network for affective body language in the macaque brain
A broadly tuned network for affective body language in the macaque brain.
No full textData and visual stimuli from the publication: *Taubert, J., Japee, S., Patterson, A., Wild, H., Goyal, S., Yu, D., Ungerleider, L. G. (accepted) A broadly tuned network for affective body language in the macaque brain
Richards, Robert J.; Daston, Lorraine (Hrsg.): Kuhn’s Structure of Scientific Revolutions at Fifty. Reflections on a Science Classic. Chicago: University of Chicago Press 2016. ISBN: 978-0-226-31720-5; 202 S.
No full textTaubert NC. Richards, Robert J.; Daston, Lorraine (Hrsg.): Kuhn’s Structure of Scientific Revolutions at Fifty. Reflections on a Science Classic. Chicago: University of Chicago Press 2016. ISBN: 978-0-226-31720-5; 202 S. H-SOZ-KULT. 06.10.2017
Richtungsweisend? Evaluierung "Radverkehrsnetz Nordrhein-Westfalen" Abschlussbericht und Tabellenband
No full textKießlich H, Städele T, Taubert NC. Richtungsweisend? Evaluierung "Radverkehrsnetz Nordrhein-Westfalen" Abschlussbericht und Tabellenband. Düsseldorf: Ministerium für Wirtschaft, Energie, Bauen, Wohnen und Verkehr des Landes Nordrhein-Westfalen.; 2007
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