Results 21 to 30 of about 7,468,732 (318)
FINET: Fast Inferring NETwork [PDF]
BMC Research Notes, 2019 Abstract Objectives Numerous software has been developed to infer the gene regulatory network, a long-standing key topic in biology and computational biology. Yet the slowness and inaccuracy inherited in current software hamper their applications to the increasing massive
Anyou Wang, Rong Hai
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DistrEdge: Speeding up Convolutional Neural Network Inference on Distributed Edge Devices [PDF]
IEEE International Parallel and Distributed Processing Symposium, 2022 As the number of edge devices with computing resources (e.g., embedded GPUs, mobile phones, and laptops) in-creases, recent studies demonstrate that it can be beneficial to col-laboratively run convolutional neural network (CNN) inference on more than ...
Xueyu Hou +3 more
semanticscholar +1 more source
A large-scale benchmark for network inference from single-cell perturbation data. [PDF]
Commun BiolMapping biological mechanisms in cellular systems is a fundamental step in early-stage drug discovery that serves to generate hypotheses on what disease-relevant molecular targets may effectively be modulated by pharmacological interventions.
Chevalley M +4 more
europepmc +2 more sources
On the Accuracy of Analog Neural Network Inference Accelerators [Feature] [PDF]
IEEE Circuits and Systems Magazine, 2021 Specialized accelerators have recently garnered attention as a method to reduce the power consumption of neural network inference. A promising category of accelerators utilizes nonvolatile memory arrays to both store weights and perform in situ analog ...
T. Xiao +7 more
semanticscholar +1 more source
Journal of Integrative Bioinformatics, 2021 Connecting transcriptional and post-transcriptional regulatory networks solves an important puzzle in the elucidation of gene regulatory mechanisms. To decipher the complexity of these connections, we build co-expression network modules for mRNA as well ...
Wani Nisar, Barh Debmalya, Raza Khalid
doaj +1 more source
Inferring cellular networks – a review [PDF]
BMC Bioinformatics, 2007 In this review we give an overview of computational and statistical methods to reconstruct cellular networks. Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts. The first part of the review deals with conditional independence models including Gaussian graphical ...
Markowetz, Florian, Spang, Rainer
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Inferring network structure from cascades [PDF]
Physical Review E, 2017 Many physical, biological, and social phenomena can be described by cascades taking place on a network. Often, the activity can be empirically observed, but not the underlying network of interactions. In this paper we offer three topological methods to infer the structure of any directed network given a set of cascade arrival times.
Ghonge, Sushrut, Vural, Dervis Can
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Meteor: Improved Secure 3-Party Neural Network Inference with Reducing Online Communication Costs
IACR Cryptology ePrint Archive, 2023 Secure neural network inference has been a promising solution to private Deep-Learning-as-a-Service, which enables the service provider and user to execute neural network inference without revealing their private inputs.
Ye Dong +4 more
semanticscholar +1 more source
Frontiers in Genetics, 2022 Accurate determination of causalities between genes is a challenge in the inference of gene regulatory networks (GRNs) from the gene expression profile.
Zhigang Jia +3 more
doaj +1 more source
Evaluating the Reproducibility of Single-Cell Gene Regulatory Network Inference Algorithms
Frontiers in Genetics, 2021 Networks are powerful tools to represent and investigate biological systems. The development of algorithms inferring regulatory interactions from functional genomics data has been an active area of research.
Yoonjee Kang +2 more
doaj +1 more source