Bayesian Optimization with Unknown Constraints

Recent work on Bayesian optimization has shown its effectiveness in global optimization of difficult black-box objective functions. Many real-world optimization problems of interest also have constraints which are unknown a priori. In this paper, we study Bayesian optimization for constrained problems in the general case that noise may be present in the constraint functions, and the objective and constraints may be evaluated independently. We provide motivating practical examples, and present a general framework to solve such problems. We demonstrate the effectiveness of our approach on optimizing the performance of online latent Dirichlet allocation subject to topic sparsity constraints, tuning a neural network given test-time memory constraints, and optimizing Hamiltonian Monte Carlo to achieve maximal effectiveness in a fixed time, subject to passing standard convergence diagnostics.Comment: 14 pages, 3 figure

Segmentation fusion for connectomics

We address the problem of automatic 3D segmentation of a stack of electron microscopy sections of brain tissue. Unlike previous efforts, where the reconstruction is usually done on a section-to-section basis, or by the agglomerative clustering of 2D segments, we leverage information from the entire volume to obtain a globally optimal 3D segmentation. To do this, we formulate the segmentation as the solution to a fusion problem. We first enumerate multiple possible 2D segmentations for each section in the stack, and a set of 3D links that may connect segments across consecutive sections. We then identify the fusion of segments and links that provide the most globally consistent segmentation of the stack. We show that this two-step approach of pre-enumeration and posterior fusion yields significant advantages and provides state-of-the-art reconstruction results. Finally, as part of this method, we also introduce a robust rotationally-invariant set of features that we use to learn and enumerate the above 2D segmentations. Our features outperform previous connectomic-specific descriptors without relying on a large set of heuristics or manually designed filter banks.Engineering and Applied Science

The Evolution of the Anopheles 16 Genomes Project

We report the imminent completion of a set of reference genome assemblies for 16 species of Anopheles mosquitoes. In addition to providing a generally useful resource for comparative genomic analyses, these genome sequences will greatly facilitate exploration of the capacity exhibited by some Anopheline mosquito species to serve as vectors for malaria parasites. A community analysis project will commence soon to perform a thorough comparative genomic investigation of these newly sequenced genomes. Completion of this project via the use of short next-generation sequence reads required innovation in both the bioinformatic and laboratory realms, and the resulting knowledge gained could prove useful for genome sequencing projects targeting other unconventional genomes

Integration of contractile forces during tissue invagination

Contractile forces generated by the actomyosin cytoskeleton within individual cells collectively generate tissue-level force during epithelial morphogenesis. During Drosophila mesoderm invagination, pulsed actomyosin meshwork contractions and a ratchet-like stabilization of cell shape drive apical constriction. Here, we investigate how contractile forces are integrated across the tissue. Reducing adherens junction (AJ) levels or ablating actomyosin meshworks causes tissue-wide epithelial tears, which release tension that is predominantly oriented along the anterior–posterior (a-p) embryonic axis. Epithelial tears allow cells normally elongated along the a-p axis to constrict isotropically, which suggests that apical constriction generates anisotropic epithelial tension that feeds back to control cell shape. Epithelial tension requires the transcription factor Twist, which stabilizes apical myosin II, promoting the formation of a supracellular actomyosin meshwork in which radial actomyosin fibers are joined end-to-end at spot AJs. Thus, pulsed actomyosin contractions require a supracellular, tensile meshwork to transmit cellular forces to the tissue level during morphogenesis.American Cancer Society (grant PF-06-143-01-DDC)National Institutes of Health (U.S.) (NIH/NIGMS, P50 grant GM071508)National Institutes of Health (U.S.) (NIH/NIGMS, R01 grant GM079340)Eunice Kennedy Shriver National Institute of Child Health and Human Development (U.S.) (grant 5R37HD15587)Howard Hughes Medical Institute (Investigator

Segmentation fusion for connectomics

We address the problem of automatic 3D segmentation of a stack of electron microscopy sections of brain tissue. Unlike previous efforts, where the reconstruction is usually done on a section-to-section basis, or by the agglomerative clustering of 2D segments, we leverage information from the entire volume to obtain a globally optimal 3D segmen-tation. To do this, we formulate the segmentation as the so-lution to a fusion problem. We first enumerate multiple pos-sible 2D segmentations for each section in the stack, and a set of 3D links that may connect segments across con-secutive sections. We then identify the fusion of segments and links that provide the most globally consistent segmen-tation of the stack. We show that this two-step approach of pre-enumeration and posterior fusion yields significant advantages and provides state-of-the-art reconstruction re-sults. Finally, as part of this method, we also introduce a robust rotationally-invariant set of features that we use to learn and enumerate the above 2D segmentations. Our fea-tures outperform previous connectomic-specific descriptors without relying on a large set of heuristics or manually de-signed filter banks. 1

RhoA GTPase inhibition organizes contraction during epithelial morphogenesis

During morphogenesis, contraction of the actomyosin cytoskeleton within individual cells drives cell shape changes that fold tissues. Coordination of cytoskeletal contractility is mediated by regulating RhoA GTPase activity. Guanine nucleotide exchange factors (GEFs) activate and GTPase-activating proteins (GAPs) inhibit RhoA activity. Most studies of tissue folding, including apical constriction, have focused on how RhoA is activated by GEFs to promote cell contractility, with little investigation as to how GAPs may be important. Here, we identify a critical role for a RhoA GAP, Cumberland GAP (C-GAP), which coordinates with a RhoA GEF, RhoGEF2, to organize spatiotemporal contractility during Drosophila melanogaster apical constriction. C-GAP spatially restricts RhoA pathway activity to a central position in the apical cortex. RhoGEF2 pulses precede myosin, and C-GAP is required for pulsation, suggesting that contractile pulses result from RhoA activity cycling. Finally, C-GAP expression level influences the transition from reversible to irreversible cell shape change, which defines the onset of tissue shape change. Our data demonstrate that RhoA activity cycling and modulating the ratio of RhoGEF2 to C-GAP are required for tissue folding.American Cancer Society (125792-RSG-14-039-01-CSM

A General Framework for Constrained Bayesian Optimization using Information-based Search

This is the author accepted manuscript. The final version is available from MIT Press via https://dl.acm.org/citation.cfm?id=2946645.3053442.We present an information-theoretic framework for solving global black-box optimization problems that also have black-box constraints. Of particular interest to us is to efficiently solve problems with decoupled constraints, in which subsets of the objective and constraint functions may be evaluated independently. For example, when the objective is evaluated on a CPU and the constraints are evaluated independently on a GPU. These problems require an acquisition function that can be separated into the contributions of the individual function evaluations. We develop one such acquisition function and call it Predictive Entropy Search with Constraints (PESC). PESC is an approximation to the expected information gain criterion and it compares favorably to alternative approaches based on improvement in several synthetic and real-world problems. In addition to this, we consider problems with a mix of functions that are fast and slow to evaluate. These problems require balancing the amount of time spent in the meta-computation of PESC and in the actual evaluation of the target objective. We take a bounded rationality approach and develop a partial update for PESC which trades off accuracy against speed. We then propose a method for adaptively switching between the partial and full updates for PESC. This allows us to interpolate between versions of PESC that are efficient in terms of function evaluations and those that are efficient in terms of wall-clock time. Overall, we demonstrate that PESC is an effective algorithm that provides a promising direction towards a unified solution for constrained Bayesian optimization.José Miguel Hernández-Lobato acknowledges support from the Rafael del Pino Foundation. Zoubin Ghahramani acknowledges support from Google Focused Research Award and EPSRC grant EP/I036575/1. Matthew W. Hoffman acknowledges support from EPSRC grant EP/J012300/1

Publishing Interactive Articles: Integrating Journals And Biological Databases

In collaboration with the journal GENETICS, we've developed and launched a pipeline by which interactive full-text HTML/PDF journal articles are published with named entities linked to corresponding resource pages in "WormBase":http://www.wormbase.org/ (WB). Our interactive articles allow a reader to click on over ten different data type objects (gene, protein, transgene, etc.) and be directed to the relevant webpage. This seamless connection from the article to summaries of data types promotes a deeper level of understanding for the naïve reader, and incisive evaluation for the sophisticated reader. Further, this collaboration allows us to identify and collect information before the publication of the article. The pipeline uses automated recognition scripts to identify entities that already exist in the database and a self-reporting form we created at WB that is sent to the author by GENETICS for submitting entities that do not already exist in our database. We include a manual quality control step to make sure ambiguous links are corrected, and that all new entities have been reported and linked properly. The automated entity recognition scripts allows us to potentially link any object found in a database as well as to expand this pipeline to other databases. We have already adapted this pipeline for linking _Saccharomyces cerevisiae_ GENETICS articles to the "Saccharomyces Genome Database":http://www.yeastgenome.org/ (SGD) and are currently expanding this pipeline for linking genes in _Drosophila_ articles to "FlyBase":http://flybase.org/. By integrating journals and databases, we are integrating the major modes of communication in the biological sciences, which will undoubtedly increase the pace of discovery.
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Should new Nuclear Reactors be considered as an option to solve Technetium shortage problem?

Worldwide, more than 80% of Nuclear Medicine procedures use a radiotracer produced through a 99Mo/99mTc generator - 99mTc – Technetium 99metastable. Most of the radiochemistry and equipments is optimized for this radioisotope characteristics already for more than 35 years, making it very difficult to replace. Worldwide production of 99Mo is based essentially with only five Nuclear Reactors that are becoming obsolete and fragile with aging, shutting down more and more frequently as they approach the end of their shelf-life. Seeking for solutions, some Governments – and the EU – plan to build new dedicated Nuclear Reactor(s). Our work defends another option