Results 51 to 60 of about 8,892,749 (345)
s2mflow: A meta-generator for multicommodity flow instances
SoftwareXBenchmark instances for multicommodity flow problems often fail to capture the structural characteristics of real-world networks or preserve a rigorous relationship with their single-commodity counterparts.
Felix P. Broesamle, Stefan Nickel
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FEBS Letters, EarlyView.Encapsulins are protein nanocompartments that play an important role in iron storage. In the Myxococcus xanthus encapsulin system, two cargo proteins called EncB and EncC contribute to iron mineralization. Here, we show that EncB and EncC generate iron‐containing minerals with distinct chemical compositions, suggesting that the composition of stored ...
Harry B. McDowell +2 more
wiley +1 more source
Running Time Analysis of MOEA/D with Crossover on Discrete Optimization Problem
AAAI Conference on Artificial Intelligence, 2019 Decomposition-based multiobjective evolutionary algorithms (MOEAs) are a class of popular methods for solving multiobjective optimization problems (MOPs), and have been widely studied in numerical experiments and successfully applied in practice. However,
Zhengxin Huang +3 more
semanticscholar +1 more source
Discrete Multiobjective Optimization [PDF]
, 2009 Multiple objective combinatorial optimization(MOCO) has become a quickly growing field in multiple objective optimization, and has recently attracted the attention of researchers both from the fields of multiple objective optimization and from single objective integer programming.
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FEBS Letters, EarlyView.How do genomes gain new functional parts? In eukaryotes, which tend to evolve under weak selection, much of the genome is junk. Palazzo and Qiu borrow the logic of Markov chains to show how non‐functional DNA becomes functional through the appearance of intermediate states, which arise due to epistasis, buffering, and biochemical messiness, allowing ...
Alexander F. Palazzo, Yi Qiu
wiley +1 more source
Sparse Gaussian Processes on Discrete Domains
IEEE Access, 2021 Kernel methods on discrete domains have shown great promise for many challenging data types, for instance, biological sequence data and molecular structure data.
Vincent Fortuin +3 more
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Convex Discrete Optimization [PDF]
, 2008 We develop an algorithmic theory of convex optimization over discrete sets. Using a combination of algebraic and geometric tools we are able to provide polynomial time algorithms for solving broad classes of convex combinatorial optimization problems and convex integer programming problems in variable dimension. We discuss some of the many applications
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Molecular Oncology, EarlyView.This study identifies somatostatin receptor 4 (Sstr4) as a critical tumor suppressor against skin and head/neck cancers (HNSCC, cSCC, and BCC). The loss of Sstr4 removes a check on cell growth, causing hyperactivation of the MAPK‐ERK signaling pathway (↑).
Ali Taqvi +6 more
wiley +1 more source
Engineering IL‐4 resistant proinflammatory human myeloid cells for cancer immunotherapy
Molecular Oncology, EarlyView.We developed a scalable workflow to generate proinflammatory human myeloid cells. CRISPR/Cas9‐edited CD34+ hematopoietic stem and progenitor cells were expanded and differentiated with M‐CSF. Deletion of STAT6 or STAT6/NFKB1 enhanced macrophage proinflammatory gene expression and cytokine secretion in the presence of IL‐4 while maintaining antibody ...
Theresa Barberi, Alan D. Friedman
wiley +1 more source
Discrete Wasserstein barycenters: optimal transport for discrete data [PDF]
Mathematical Methods of Operations Research, 2016 Wasserstein barycenters correspond to optimal solutions of transportation problems for several marginals, and as such have a wide range of applications ranging from economics to statistics and computer science. When the marginal probability measures are absolutely continuous (or vanish on small sets) the theory of Wasserstein barycenters is well ...
Ethan B. Anderes +2 more
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