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1703 Publications visible to you, out of a total of 1703
Drug Metabolism Prediction

Abstract

Not specified

Authors: Ghulam Mustafa, Xiaofeng Yu, Rebecca C. Wade

Date Published: 11th Jul 2014

Publication Type: InBook

Data extraction for the reaction kinetics database SABIO-RK

Abstract (Expand)

SABIO-RK (http://sabio.h-its.org/) is a web-accessible, manually curated database that has been established as a resource for biochemical reactions and their kinetic properties with a focus on supporting … the computational modeling to create models of biochemical reaction networks. SABIO-RK data are mainly extracted from literature but also directly submitted from lab experiments. In most cases the information in the literature is distributed across the whole publication, insufficiently structured and often described without standard terminology. Therefore the manual extraction of knowledge from the literature requires biological experts to understand the paper and interpret the data. The database offers the literature data in a structured format including annotations to controlled vocabularies, ontologies and external databases which supports modellers, as well as experimentalists, in the very time consuming process of collecting information from different publications. Here we describe the data extraction and curation efforts needed for SABIO-RK and give recommendations for publishing kinetic data in a complete and structured manner.

Authors: Ulrike Wittig, Renate Kania, Meik Bittkowski, Elina Wetsch, Lei Shi, Lenneke Jong, Martin Golebiewski, Maja Rey, Andreas Weidemann, Isabel Rojas, Wolfgang Müller

Date Published: 1st May 2014

Publication Type: Journal

Improving the performance of photometric regression models via massive parallel feature selection

Abstract (Expand)

Regression tasks are common in astronomy, for instance, the estimation of the redshift or the metallicity of galaxies. Generating regression models, however, is often hindered by the heterogeneity of … the available input catalogs, which leads to missing data and/or features of differing explanatory power. In this work, we show how simple but effective feature selection schemes from data mining can be used to significantly improve the performance of regression models for photometric redshift and metallicity estimation (even without any particular knowledge of the input parameters' physical properties). Our framework tests huge amounts of possible feature combinations. Since corresponding (single-core) implementations are computationally very demanding, we make use of the massive computational resources provided by nowadays graphics processing units to significantly reduce the overall runtime. This renders an exhaustive search possible, as we demonstrate in our experimental evaluation. We conclude the work by discussing further applications of our approach in the context of large-scale astronomical learning settings.

Authors: K. L. Polsterer, F. Gieseke, Christian Igel, Tomotsugu Goto

Date Published: 1st May 2014

Publication Type: InProceedings

Speedy Greedy Feature Selection: Better Redshift Estimation via Massive Parallelism

Abstract (Expand)

Nearest neighbor models are among the most basic tools in machine learning, and recent work has demonstrated their effectiveness in the field of astronomy. The performance of these models crucially … depends on the underlying metric, and in particular on the selection of a meaningful subset of informative features. The feature selection is task-dependent and usually very time-consuming. In this work, we propose an efficient parallel implementation of incremental feature selection for nearest neighbor models utilizing nowadays graphics processing units. Our framework provides significant computational speed-ups over its sequential single-core competitor of up to two orders of magnitude. We demonstrate the applicability of the overall scheme on one of the most challenging tasks in astronomy: redshift estimation for distant galaxies.

Authors: F. Gieseke, Kai L. Polsterer, Cosmin Eugen Oancea, Christian Igel

Date Published: 17th Mar 2014

Publication Type: InProceedings

Meeting report from the fourth meeting of the Computational Modeling in Biology Network (COMBINE)

Abstract

Not specified

Authors: Dagmar Waltemath, Frank T. Bergmann, Claudine Chaouiya, Tobias Czauderna, Padraig Gleeson, Carole Goble, Martin Golebiewski, Michael Hucka, Nick Juty, Olga Krebs, Nicolas Le Novère, Huaiyu Mi, Ion I. Moraru, Chris J. Myers, David Nickerson, Brett G. Olivier, Nicolas Rodriguez, Falk Schreiber, Lucian Smith, Fengkai Zhang, Eric Bonnet

Date Published: 15th Mar 2014

Publication Type: Journal

Calibration of ECMWF forecasts

Abstract

Not specified

Authors: D. Richardson, S. Hemri, K. Bogner, T. Gneiting, T. Haiden, F. Pappenberger, M. Scheuerer

Date Published: 2014

Publication Type: Journal

Desorption Electrospray Ionisation Mass Spectrometry of Stabilised Polyesters Reveals Activation of Hindered Amine Light Stabilisers

Abstract (Expand)

The use of hindered amine light stabilizers (HALS) to retard thermo- and photo-degradation of polymers has become increasingly common. Proposed mechanisms of polymer stabilisation involve significant … changes to the HALS chemical structure; however, reports of the characterisation of these modified chemical species are limited. To better understand the fate of HALS and determine their in situ modifications, desorption electrospray ionisation mass spectrometry (DESI-MS) was employed to characterise ten commercially available HALS present in polyester-based coil coatings. TINUVIN® 770, 292, 144, 123, 152, and NOR371; HOSTAVIN® 3052, 3055, 3050, and 3058 were separately formulated with a pigmented, thermosetting polyester resin, cured on metal at 262 °C and analysed directly by DESI-MS. High-level ab initio molecular orbital theory calculations were also undertaken to aid the mechanistic interpretation of the results. For HALS containing N-substituted piperidines (i.e., N–CH3, N–C(O)CH3, and N–OR) a secondary piperidine (N–H) analogue was detected in all cases. The formation of these intermediates can be explained either through hydrogen abstraction based mechanisms or direct N–OR homolysis with the former dominant under normal service temperatures (ca. 25–80 °C), and the latter potentially becoming competitive under the high temperatures associated with curing (ca. 230–260 °C).

Authors: Martin R.L. Paine, Ganna Gryn'ova, Michelle L. Coote, Philip J. Barker, Stephen J. Blanksby

Date Published: 2014

Publication Type: Journal

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