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Network Inference With the Lasso. [PDF]
Multivariate Behav Res, 2022 Calculating confidence intervals and p-values of edges in networks is useful to decide their presence or absence and it is a natural way to quantify uncertainty. Since Lasso estimation is often used to obtain edges in a network, and the underlying distribution of Lasso estimates is discontinuous and has probability one at zero when the estimate is zero,
Waldorp L, Haslbeck J.
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Node Metadata Can Produce Predictability Crossovers in Network Inference Problems [PDF]
Physical Review X, 2022 Network inference is the process of learning the properties of complex networks from data. Besides using information about known links in the network, node attributes and other forms of network metadata can help solve network inference problems.
Oscar Fajardo-Fontiveros +2 more
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Bayesian networks for network inference in biology. [PDF]
J R Soc InterfaceBayesian networks (BNs) have been used for reconstructing interactions from biological data, in disciplines ranging from molecular biology to ecology and neuroscience. BNs learn conditional dependencies between variables, which best ‘explain’ the data, represented as a directed graph which approximates the relationships between variables. In the 2000s,
Hammond J, Smith VA.
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GTAT-GRN: a graph topology-aware attention method with multi-source feature fusion for gene regulatory network inference [PDF]
Frontiers in GeneticsGene regulatory network (GRN) inference is a central task in systems biology. However, due to the noisy nature of gene expression data and the diversity of regulatory structures, accurate GRN inference remains challenging. We hypothesize that integrating
Shuran Wang +17 more
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Optimized network inference for immune diseased single cells [PDF]
Frontiers in ImmunologyIntroductionMathematical models are powerful tools that can be used to advance our understanding of complex diseases. Autoimmune disorders such as systemic lupus erythematosus (SLE) are highly heterogeneous and require high-resolution mechanistic ...
Elena Merino Tejero +10 more
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Plugging Small RNAs into the Network
mSystems, 2020 Small RNAs (sRNAs) have been discovered in every bacterium examined and have been shown to play important roles in the regulation of a diverse range of behaviors, from metabolism to infection.
Lars Barquist
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Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation
mSystems, 2023 Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these
Dileep Kishore +5 more
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Network Cluster‐Robust Inference [PDF]
Econometrica, 2021 Since network data commonly consists of observations from a single large network, researchers often partition the network into clusters in order to apply cluster‐robust inference methods. Existing such methods require clusters to be asymptotically independent. Under mild conditions, we prove that, for this requirement to hold for network‐dependent data,
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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
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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
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