Reproducible computational biology experiments with SED-ML - The Simulation Experiment Description Markup Language

Background: The increasing use of computational simulation experiments to inform modern biological research creates new challenges to annotate, archive, share and reproduce such experiments. The recently published Minimum Information About a Simulation Experiment (MIASE) proposes a minimal set of information that should be provided to allow the reproduction of simulation experiments among users and software tools. Results: In this article, we present the Simulation Experiment Description Markup Language (SED-ML). SED-ML encodes in a computer-readable exchange format the information required by MIASE to enable reproduction of simulation experiments. It has been developed as a community project and it is defined in a detailed technical specification and additionally provides an XML schema. The version of SED-ML described in this publication is Level 1 Version 1. It covers the description of the most frequent type of simulation experiments in the area, namely time course simulations. SED-ML documents specify which models to use in an experiment, modifications to apply on the models before using them, which simulation procedures to run on each model, what analysis results to output, and how the results should be presented. These descriptions are independent of the underlying model implementation. SED-ML is a software-independent format for encoding the description of simulation experiments; it is not specific to particular simulation tools. Here, we demonstrate that with the growing software support for SED-ML we can effectively exchange executable simulation descriptions. Conclusions: With SED-ML, software can exchange simulation experiment descriptions, enabling the validation and reuse of simulation experiments in different tools. Authors of papers reporting simulation experiments can make their simulation protocols available for other scientists to reproduce the results. Because SED-ML is agnostic about exact modeling language(s) used, experiments covering models from different fields of research can be accurately described and combined

Towards a Dynamic Data Structure for Efficient Bounded Line Range Search

Abstract We present a data structure for efficient axis-aligned orthogonal range search on a set of n lines in a bounded plane. The algorithm requires O(log n + k) time in the worst case to find all lines intersecting an axis aligned query rectangle R, where k is the number of lines in range. O(n + λ) space is required for the data structure used by the algorithm, where λ is the number of intersection points among the lines. Insertion of a new rightmost line or deletion of a leftmost line requires O(n) time in the worst case. For a sparse arrangement of lines (i.e., for λ = O(n)), insertion of a rightmost line or deletion of a leftmost line requires O( √ n) time, and O(log n + µ) expected time for µ the number of intersection points between and existing lines

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016

Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016

Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them

Genetic variation in Caveolin-1 correlates with long-term pancreas transplant outcome

Pancreas transplantation is a successful treatment for a selected group of people with type 1 diabetes. Continued insulin production can decrease over time and identifying predictors of long-term graft function is key to improving survival. The aim of this study was to screen subjects for variation in the Caveolin-1 gene (Cav1), previously shown to correlate with long-term kidney transplant function. We genotyped 435 pancreas transplant donors and 431 recipients who had undergone pancreas transplantation at the Oxford Transplant Centre, UK, for all known common variation in Cav1. Death-censored cumulative events were analyzed using Kaplan-Meier and Cox regression. Unlike kidney transplantation, the rs4730751 variant in our pancreas donors or transplant recipients did not correlate with long-term graft function (p = 0.331-0.905). Presence of rs3801995 TT genotype (p = 0.009) and rs9920 CC/CT genotype (p = 0.010) in our donors did however correlate with reduced long-term graft survival. Multivariate Cox regression (adjusted for donor and recipient transplant factors) confirmed the association of rs3801995 (p = 0.009, HR = 1.83;[95% CI = 1.16-2.89]) and rs9920 (p = 0.037, HR = 1.63; [95% CI = 1.03-2.73]) with long-term graft function. This is the first study to provide evidence that donor Cav1 genotype correlates with long-term pancreas graft function. Screening Cav1 in other datasets is required to confirm these pilot results

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016

Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them