134 research outputs found
A simplicial homology algorithm for Lipschitz optimisation
The simplicial homology global optimisation (SHGO) algorithm is a general purpose global optimisation algorithm based on applications of simplicial integral homology and combinatorial topology. SHGO approximates the homology groups of a complex built on a hypersurface homeomorphic to a complex on the objective function. This provides both approximations of locally convex subdomains in the search space through Spernerâs lemma and a useful visual tool for characterising and efficiently solving higher dimensional black and grey box optimisation problems. This complex is built up using sampling points within the feasible search space as vertices. The algorithm is specialised in finding all the local minima of an objective function with expensive function evaluations efficiently which is especially suitable to applications such as energy landscape exploration. SHGO was initially developed as an improvement on the topographical global optimisation (TGO) method. It is proven that the SHGO algorithm will always outperform TGO on function evaluations if the objective function is Lipschitz smooth. In this paper SHGO is applied to non-convex problems with linear and box constraints with bounds placed on the variables. Numerical experiments on linearly constrained test problems show that SHGO gives competitive results compared to TGO and the recently developed Lc-DISIMPL algorithm as well as the PSwarm, LGO and DIRECT-L1 algorithms. Furthermore SHGO is compared with the TGO, basinhopping (BH) and differential evolution (DE) global optimisation algorithms over a large selection of black-box problems with bounds placed on the variables from the SciPy benchmarking test suite. A Python implementation of the SHGO and TGO algorithms published under a MIT license can be found from https://bitbucket.org/upiamcompthermo/shgo/.http://link.springer.com/journal/108982019-10-01hj2018Chemical Engineerin
Cosmological bounds on large extra dimensions from non-thermal production of Kaluza-Klein modes
The existing cosmological constraints on theories with large extra dimensions
rely on the thermal production of the Kaluza-Klein modes of gravitons and
radions in the early Universe. Successful inflation and reheating, as well as
baryogenesis, typically requires the existence of a TeV-scale field in the
bulk, most notably the inflaton. The non-thermal production of KK modes with
masses of order 100 GeV accompanying the inflaton decay sets the lower bounds
on the fundamental scale M_*. For a 1 TeV inflaton, the late decay of these
modes distort the successful predictions of Big Bang Nucleosynthesis unless
M_*> 35, 13, 7, 5 and 3 TeV for 2, 3, 4, 5 and 6 extra dimensions,
respectively. This improves the existing bounds from cosmology on M_* for 4, 5
and 6 extra dimensions. Even more stringent bounds are derived for a heavier
inflaton.Comment: 17 pages, latex, 4 figure
Bifurcated topological optimization for IVIM
In this work, we shed light on the issue of estimating Intravoxel Incoherent Motion (IVIM)
for diffusion and perfusion estimation by characterizing the objective function using
simplicial homology tools. We provide a robust solution via topological optimization of
this model so that the estimates are more reliable and accurate. Estimating the tissue
microstructure from diffusion MRI is in itself an ill-posed and a non-linear inverse problem.
Using variable projection functional (VarPro) to fit the standard bi-exponential IVIM model
we perform the optimization using simplicial homology based global optimization to
better understand the topology of objective function surface. We theoretically show
how the proposed methodology can recover the model parameters more accurately
and consistently by casting it in a reduced subspace given by VarPro. Additionally
we demonstrate that the IVIM model parameters cannot be accurately reconstructed
using conventional numerical optimization methods due to the presence of infinite
solutions in subspaces. The proposed method helps uncover multiple global minima by
analyzing the local geometry of the model enabling the generation of reliable estimates
of model parameters.The National Institute of Biomedical Imaging And Bioengineering (NIBIB) of the National Institutes of Health (NIH); University of Washingtonâs Royalty Research Fund; NIH grants; the German Research Foundation (DFG) and a grant from the Alfred P. Sloan Foundation and the Gordon & Betty Moore Foundation to the University of Washington eScience Institute Data Science Environment.http://www.frontiersin.org/Neuroscienceam2022Chemical Engineerin
A Next Step in Disruption Management: Combining Operations Research and Complexity Science
Railway systems occasionally get into a state of out-of-control, meaning that there is
barely any train is running, even though the required resources (infrastructure, rolling
stock and crew) are available. These situations can either be caused by large disruptions
or unexpected propagation and accumulation of delays. Because of the large number
of aected resources and the absence of detailed, timely and accurate information,
currently existing methods cannot be applied in out-of-control situations. Most of the
contemporary approaches assume that there is only one single disruption with a known
duration, that all information about the resources is available, and that all stakeholders
in the operations act as expected. Another limitation is the lack of knowledge about
why and how disruptions accumulate and whether this process can be predicted. To
tackle these problems, we develop a multidisciplinary framework aiming at reducing
the impact of these situations and - if possible - avoiding them. The key elements
of this framework are (i) the generation of early warning signals for out-of-control
situations using tools from complexity science and (ii) a set of rescheduling measures
robust against the features of out-of-control situations, using tools from operations
research
A next step in disruption management: combining operations research and complexity science
Railway systems occasionally get into a state of being out-of-control, meaning that barely any train is running, even though the required resources (infrastructure, rolling stock and crew) are available. Because of the large number of affected resources and the absence of detailed, timely and accurate information, currently existing disruption management techniques cannot be applied in out-of-control situations. Most of the contemporary approaches assume that there is only one single disruption with a known duration, that all information about the resources is available, and that all stakeholders in the operations act as expected. Another limitation is the lack of knowledge about why and how disruptions accumulate and whether this process can be predicted. To tackle these problems, we develop a multidisciplinary framework combining techniques from complexity science and operations research, aiming at reducing the impact of these situations andâif possibleâavoiding them. The key elements of this framework are (i) the generation of early warning signals for out-of-control situations, (ii) isolating a specific region such that delay stops propagating, and (iii) the app
RAS and BRAF mutations in cell-free DNA are predictive for outcome of cetuximab monotherapy in patients with tissue-tested RAS wild-type advanced colorectal cancer
In metastatic colorectal cancer, RAS and BRAF mutations cause resistance to anti-EGFR therapies, such as cetuximab. Heterogeneity in RAS and BRAF mutations might explain nonresponse in a subset of patients receiving cetuximab. Analyzing mutations in plasma-derived circulating tumor DNA (ctDNA) could provide a more comprehensive overview of the mutational landscape as compared to analyses of primary and/or metastatic tumor tissue. Therefore
The Polygenic and Monogenic Basis of Blood Traits and Diseases
Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation. Analysis of blood cell traits in the UK Biobank and other cohorts illuminates the full genetic architecture of hematopoietic phenotypes, with evidence supporting the omnigenic model for complex traits and linking polygenic burden with monogenic blood diseases
Fine-Scale Mapping of the 4q24 Locus Identifies Two Independent Loci Associated with Breast Cancer Risk
Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored.
Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium.
Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 Ă 10â4; OR, 1.04; 95% confidence interval (CI), 1.02â1.07] and rs77928427 (P = 1.86 Ă 10â4; OR, 1.04; 95% CI, 1.02â1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 â„ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factorâbinding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue.
Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2.
Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk
ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors
Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure
Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies
- âŠ