Results 81 to 90 of about 158,513 (260)
A Gradient System for Low Rank Matrix Completion
Axioms, 2018 In this article we present and discuss a two step methodology to find the closest low rank completion of a sparse large matrix. Given a large sparse matrix M, the method consists of fixing the rank to r and then looking for the closest rank-r matrix X to
Carmela Scalone, Nicola Guglielmi
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Molecular Oncology, EarlyView.Cytarabine is a key therapy for acute myeloid leukaemia (AML), but its efficacy is limited by the dNTPase SAMHD1, which hydrolyses its active metabolite. Screening nucleotide biosynthesis inhibitors revealed that IMPDH inhibitors selectively sensitise SAMHD1‐proficient AML cells to cytarabine.
Miriam Yagüe‐Capilla +9 more
wiley +1 more source
Fast Exact Matrix Completion: A Unified Optimization Framework for Matrix Completion
, 2019 We formulate the problem of matrix completion with and without side information as a non-convex optimization problem. We design fastImpute based on non-convex gradient descent and show it converges to a global minimum that is guaranteed to recover closely the underlying matrix while it scales to matrices of sizes beyond $10^5 \times 10^5$.
Bertsimas, D, Li, ML
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Molecular Oncology, EarlyView.Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch +13 more
wiley +1 more source
Survey of Matrix Completion Algorithms
CoRR, 2022 Matrix completion problem has been investigated under many different conditions since Netflix announced the Netflix Prize problem. Many research work has been done in the field once it has been discovered that many real life dataset could be estimated with a low-rank matrix.
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Molecular Oncology, EarlyView.We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric +10 more
wiley +1 more source
RW-MC:self-adaptive random walk based matrix completion algorithm
Tongxin xuebao, 2017 Concerning the continually perceiving performance of virtual access points (VAP) was urgent in software-defined wireless network (SDWN),with the features of VAPs’ measurement data (VMD),a self-adaptive matrix completion algorithm based on random walk was
Xin-heng WANG +4 more
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Molecular Oncology, EarlyView.Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary +1 more
wiley +1 more source
Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
iMTF-GRN: Integrative Matrix Tri-Factorization for Inference of Gene Regulatory Networks
IEEE Access, 2019 Gene Regulatory Network (GRN) inference using computational approaches has been a highly pursued problem in bioinformatics. Various approaches have been developed to infer GRNs from gene expression data including statistical, machine learning and ...
Nisar Wani, Khalid Raza
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