Results 11 to 20 of about 7,468,732 (318)
Frontiers in Genetics, 2023 Gene regulatory networks are graph models representing cellular transcription events. Networks are far from complete due to time and resource consumption for experimental validation and curation of the interactions.
Juan M. Escorcia-Rodríguez +9 more
doaj +2 more sources
A Survey of Quantization Methods for Efficient Neural Network Inference [PDF]
Low-Power Computer Vision, 2021 As soon as abstract mathematical computations were adapted to computation on digital computers, the problem of efficient representation, manipulation, and communication of the numerical values in those computations arose.
A. Gholami +5 more
semanticscholar +1 more source
NeuJeans: Private Neural Network Inference with Joint Optimization of Convolution and FHE Bootstrapping [PDF]
Conference on Computer and Communications Security, 2023 Fully homomorphic encryption (FHE) is a promising cryptographic primitive for realizing private neural network inference (PI) services by allowing a client to fully offload the inference task to a cloud server while keeping the client data oblivious to ...
Jae Hyung Ju +6 more
semanticscholar +1 more source
Identifiability of complex networks
Frontiers in Physics, 2023 We discuss the core principles underpinning the concept of identifiability, providing an overview of relevant literature concerning this phenomenon within the domain of complex networks.
M. Zanin, J. M. Buldú, J. M. Buldú
doaj +1 more source
Dissecting cell identity via network inference and in silico gene perturbation
Nature, 2023 A machine-learning-based strategy called CellOracle combines computational perturbation with modelling of gene-regulatory networks to analyse how cell identity is regulated by transcription factors, and correctly predicts phenotypic changes after ...
Kenji Kamimoto +5 more
semanticscholar +1 more source
Metabolites, 2023 Colorectal cancer (CRC), one of the most prevalent and deadly cancers worldwide, generally evolves from adenomatous polyps. The understanding of the molecular mechanisms underlying this pathological evolution is crucial for diagnostic and prognostic ...
Francesca Di Cesare +4 more
doaj +1 more source
CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data [PDF]
arXiv.org, 2022 Causal inference is a vital aspect of multiple scientific disciplines and is routinely applied to high-impact applications such as medicine. However, evaluating the performance of causal inference methods in real-world environments is challenging due to ...
Mathieu Chevalley +4 more
semanticscholar +1 more source
Network neutrality inference [PDF]
ACM SIGCOMM Computer Communication Review, 2014 When can we reason about the neutrality of a network based on external observations? We prove conditions under which it is possible to (a) detect neutrality violations and (b) localize them to specific links, based on external observations. Our insight is that, when we make external observations from different vantage points, these will most likely be ...
Zhang Zhiyong +2 more
openaire +3 more sources
Single-cell biological network inference using a heterogeneous graph transformer
Nature Communications, 2023 Single-cell multi-omics and deep learning could lead to the inference of biological networks across specific cell types. Here, the authors develop DeepMAPS, a deep learning, graph-based approach for cell-type specific network inference from single-cell ...
A. Ma +19 more
semanticscholar +1 more source
Microorganisms, 2021 Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory machinery. The study of such machinery at the global scale has been challenged by the lack of data integration. Here, we
Juan M. Escorcia-Rodríguez +2 more
doaj +1 more source