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Inferring network interactions within a cell

G. W. Carter
2005 Briefings in Bioinformatics  
These networks involve distinct interaction types detected by a combination of methods, ranging from directly observed physical interactions based in biochemistry to interactions inferred from phenotype  ...  Considering yeast as a model system, recent analytical methods are reviewed here and specific aims are proposed to improve network interaction inference and facilitate predictive biological modelling.  ...  Genetic interactions are manifestations of many regulatory and functional interactions at work within a biochemical pathway or network, observed indirectly by comparing phenotype variation between genotypes  ... 
doi:10.1093/bib/6.4.380 pmid:16420736 fatcat:dlklcwolsbcxniihijty22kh4u

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks

Anthony Deeter, Mark Dalman, Joseph Haddad, Zhong-Hui Duan, Frank Alexander Feltus
2017 PLoS ONE  
The structure of a Bayesian network can be representative of the interactions among genes within a biological pathway.  ...  We have created a system with which to combine the statistical power of Bayesian networks with the genetic information contained within citations accessible from the PubMed database in order to infer interactions  ...  As shown in Fig 10, using a resolution of 0.90, 35 inferred interactions are present within the consensus network.  ... 
doi:10.1371/journal.pone.0186004 pmid:29049295 pmcid:PMC5648141 fatcat:33xczuvkwbak3afyrapd7wx4xu

Network modeling of single-cell omics data: challenges, opportunities, and progresses

Montgomery Blencowe, Douglas Arneson, Jessica Ding, Yen-Wei Chen, Zara Saleem, Xia Yang
2019 Emerging Topics in Life Sciences  
and cell-cell interaction or communication networks.  ...  Gene regulatory network modeling has been used as a powerful approach to elucidate the complex molecular interactions underlying biological processes and systems, yet its application in single-cell omics  ...  Gene networks within a given cell population and cell-cell communication networks can also be reconstructed based on various assumptions and algorithms.  ... 
doi:10.1042/etls20180176 pmid:32270049 pmcid:PMC7141415 fatcat:x47pn56f6fbhxkzb3vcze3cuuq

Gene networks in cancer are biased by aneuploidies and sample impurities [article]

Michael Schubert, Maria Colome-Tatche, Floris Foijer
2019 bioRxiv   pre-print
Gene regulatory network inference is a standard technique for obtaining structured regulatory information from, among other data sources, gene expression measurements.  ...  Here, we take networks inferred from TCGA cohorts as an example to show that (1) transcription factor annotations are essential to obtaining reliable networks, and (2) even when taking these into account  ...  Quantifying possible TF-TG interactions To quantify enrichment of real (obtained from ChIP binding experiments) TF-TG interactions within the top genes of a given network, we first need to enumerate the  ... 
doi:10.1101/752816 fatcat:3ladhlapi5ddnoat7o2i6qrqgy

Algorithmic Reconstruction of GBM Network Complexity [article]

Abicumaran Uthamacumaran, Morgan Craig
2021 bioRxiv   pre-print
Here, we applied a host of data theoretic techniques, including clustering algorithms, Waddington landscape reconstruction, trajectory inference algorithms, and network approaches, to compare gene expression  ...  Our study is among the first to provide strong evidence of the applicability of complex systems approaches for reverse-engineering gene networks from patient-derived single-cell datasets and inferring  ...  PIDC network inference uses partial information decomposition (PID) to infer regulatory interaction networks from gene expression datasets.  ... 
doi:10.1101/2021.09.21.461255 fatcat:vho7hhwwc5dtxcd3jy2nlch7q4

INBIA: a boosting methodology for proteomic network inference

Davide S. Sardina, Giovanni Micale, Alfredo Ferro, Alfredo Pulvirenti, Rosalba Giugno
2018 BMC Bioinformatics  
Results: We have developed a methodology called Inference Network Based on iRefIndex Analysis (INBIA) to accurately correlate proteomic inferred relations to protein-protein interaction (PPI) networks.  ...  However, established protocols to infer interaction networks from protein expressions are still missing.  ...  In general, these modifications affect the cellular processes by regulating protein-protein interactions (PPIs) being a remarkable key component in cell signaling, especially when dealing with cancer cells  ... 
doi:10.1186/s12859-018-2183-5 pmid:30066650 pmcid:PMC6069689 fatcat:slcdeza2pjfpdl7znbcdeemy4q

Single-cell interactomes of the human brain reveal cell-type specific convergence of brain disorders [article]

Shahin Mohammadi, Jose Davila-Velderrain, Manolis Kellis
2019 bioRxiv   pre-print
Emerging single-cell profiling technologies, which survey the transcriptional cell-state distribution of complex tissues, could be used to infer the single-cell context of gene interactions.  ...  Here we introduce SCINET (Single-Cell Imputation and NETwork construction), a computational framework that reconstructs an ensemble of cell type-specific interactomes by integrating a global, context-independent  ...  Patterns of specificity of identified interactions. a, summary of inferred cell-type specific networks. b, patterns of connectivity and interaction strength computed within cell-type specific networks  ... 
doi:10.1101/586859 fatcat:3uvbuuaearftjkklzvoeeky6o4

Cell lineage and communication network inference via optimization for single-cell transcriptomics

Shuxiong Wang, Matthew Karikomi, Adam L MacLean, Qing Nie
2019 Nucleic Acids Research  
SoptSC then predicts cell-cell communication networks, enabling reconstruction of complex cell lineages that include feedback or feedforward interactions.  ...  are inferred via a structured cell-to-cell similarity matrix.  ...  within a sample.  ... 
doi:10.1093/nar/gkz204 pmid:30923815 pmcid:PMC6582411 fatcat:h5ilxo7btrdexo57er7hre6bii

An Interspecies Regulatory Network Inferred from Simultaneous RNA-seq of Candida albicans Invading Innate Immune Cells

Lanay Tierney, Jörg Linde, Sebastian Müller, Sascha Brunke, Juan Camilo Molina, Bernhard Hube, Ulrike Schöck, Reinhard Guthke, Karl Kuchler
2012 Frontiers in Microbiology  
A robust network inference map was generated from this dataset using NetGenerator, predicting novel interactions between the host and the pathogen.  ...  Remarkably, binding of recombinant Ptx3 to the C. albicans cell wall was found to regulate the expression of fungal Hap3 target genes as predicted by the network inference model.  ...  Of all of the candidate cell surface Hap3 targets, only Cda2, a putative chitin deacetylase forms a robust interaction with Hap3 within the second network (Figure A3 in Appendix).  ... 
doi:10.3389/fmicb.2012.00085 pmid:22416242 pmcid:PMC3299011 fatcat:6prhgvsmlze7tbkzzhh3mwzmie

DTNI: a novel toxicogenomics data analysis tool for identifying the molecular mechanisms underlying the adverse effects of toxic compounds

Diana M. Hendrickx, Terezinha Souza, Danyel G. J. Jennen, Jos C. S. Kleinjans
2016 Archives of Toxicology  
induced by a group of compounds influencing a common biological process.  ...  Furthermore, DTNI also discloses several unknown interactions which have to be verified experimentally.  ...  Acknowledgements This work was supported by EXPOsOMICS, a part of the EU Seventh Framework Programme, under Grant Agreement No. 308610.  ... 
doi:10.1007/s00204-016-1922-5 pmid:28032149 pmcid:PMC5429357 fatcat:wjhrpan2zfdjxdz4ws4jvqzshm

Toward the dynamic interactome: it's about time

T. M. Przytycka, M. Singh, D. K. Slonim
2010 Briefings in Bioinformatics  
Dynamic molecular interactions play a central role in regulating the functioning of cells and organisms.  ...  Here we review the beginnings of a new subfield within computational biology, one focused on the global inference and analysis of the dynamic interactome.  ...  Acknowledgements This article was inspired by our involvement in the Pacific Symposium on Biocomputing session 'Dynamics of Biological Networks', which we are co-organizing with Tanya Berger-Wolf (University  ... 
doi:10.1093/bib/bbp057 pmid:20061351 pmcid:PMC2810115 fatcat:xbj7ugs6nbed7guys2ie5z3efa

New avenues for systematically inferring cell-cell communication: through single-cell transcriptomics data

Xin Shao, Xiaoyan Lu, Jie Liao, Huajun Chen, Xiaohui Fan
2020 Protein & Cell  
We first summarize a common workflow of cell-cell communication study using scRNA-seq data, which often includes data preparation, construction of communication networks, and result validation.  ...  complex tissues, which enables systematic cell-cell communication studies at a single-cell level.  ...  to a distribution for each type of interaction in the network.  ... 
doi:10.1007/s13238-020-00727-5 pmid:32435978 fatcat:gu7rpbzxfbeujeplsaqtx35eni

A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data

Yongli Hu, Takeshi Hase, Hui Peng Li, Shyam Prabhakar, Hiroaki Kitano, See Kiong Ng, Samik Ghosh, Lawrence Jin Kiat Wee
2016 BMC Genomics  
Further downstream network reconstruction analysis was carried out to unravel hidden general regulatory networks where novel interactions could be further validated in web-lab experimentation and be useful  ...  It is believed to be extensible and applicable to other single-cell RNA-seq expression profiles like that of the study of the cancer progression and treatment within a highly heterogeneous tumour.  ...  cells within a tumour [18] .  ... 
doi:10.1186/s12864-016-3317-7 pmid:28155657 pmcid:PMC5260093 fatcat:z747ov5elrgdxhqyba6qwjfdau

MINI-EX: Integrative inference of single-cell gene regulatory networks in plants [article]

Camilla Ferrari, Nicolas Manosalva Perez, Klaas Vandepoele
2022 bioRxiv   pre-print
and crops, we developed MINI-EX (Motif-Informed Network Inference based on single-cell EXpression data), an integrative approach to infer cell-type specific networks in plants.  ...  We demonstrate MINI-EX's stability towards input data sets with low number of cells and its robustness towards missing data, and we show it infers state-of-the-art networks with a better performance compared  ...  in a number of cells within the cluster to be regulatory active.  ... 
doi:10.1101/2022.07.01.498402 fatcat:7pkefqvgljaldcfg5smk2g7xie

Integrative construction of regulatory region networks in 127 human reference epigenomes by matrix factorization [article]

Dianbo Liu, Jose Davila-Velderrain, ZHizhuo Zhang, Manolis Kellis
2017 bioRxiv   pre-print
The framework was used to predict a regulatory network of chromatin interaction edges linking more than 20,000 promoters and 1.8 million enhancers across 127 human reference epigenomes, including edges  ...  Here, we introduce a matrix factorization framework to integrate physical and functional interaction data of genomic segments.  ...  factories within the cell (32) .  ... 
doi:10.1101/217588 fatcat:5ewbnp5kx5hvnomkepswtg2rau
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