NPJ Systems Biology and Applications最新文献_第7页

Revisiting the evolution of bow-tie architecture in signaling networks. 重新审视信号网络中蝴蝶结结构的演变。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-29 DOI: 10.1038/s41540-024-00396-8

Thoma Itoh, Yohei Kondo, Kazuhiro Aoki, Nen Saito

{"title":"Revisiting the evolution of bow-tie architecture in signaling networks.","authors":"Thoma Itoh, Yohei Kondo, Kazuhiro Aoki, Nen Saito","doi":"10.1038/s41540-024-00396-8","DOIUrl":"10.1038/s41540-024-00396-8","url":null,"abstract":"Bow-tie architecture is a layered network structure that has a narrow middle layer with multiple inputs and outputs. Such structures are widely seen in the molecular networks in cells, suggesting that a universal evolutionary mechanism underlies the emergence of bow-tie architecture. The previous theoretical studies have implemented evolutionary simulations of the feedforward network to satisfy a given input-output goal and proposed that the bow-tie architecture emerges when the ideal input-output relation is given as a rank-deficient matrix with mutations in network link intensities in a multiplicative manner. Here, we report that the bow-tie network inevitably appears when the link intensities representing molecular interactions are small at the initial condition of the evolutionary simulation, regardless of the rank of the goal matrix. Our dynamical system analysis clarifies the mechanisms underlying the emergence of the bow-tie structure. Further, we demonstrate that the increase in the input-output matrix reduces the width of the middle layer, resulting in the emergence of bow-tie architecture, even when evolution starts from large link intensities. Our data suggest that bow-tie architecture emerges as a side effect of evolution rather than as a result of evolutionary adaptation.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11217396/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141477071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. 纵向单细胞数据为炎症性肠病的确定性建模提供了信息。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-24 DOI: 10.1038/s41540-024-00395-9

Christoph Kilian, Hanna Ulrich, Viktor A Zouboulis, Paulina Sprezyna, Jasmin Schreiber, Tomer Landsberger, Maren Büttner, Moshe Biton, Eduardo J Villablanca, Samuel Huber, Lorenz Adlung

{"title":"Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease.","authors":"Christoph Kilian, Hanna Ulrich, Viktor A Zouboulis, Paulina Sprezyna, Jasmin Schreiber, Tomer Landsberger, Maren Büttner, Moshe Biton, Eduardo J Villablanca, Samuel Huber, Lorenz Adlung","doi":"10.1038/s41540-024-00395-9","DOIUrl":"10.1038/s41540-024-00395-9","url":null,"abstract":"Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11196733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141446646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA damage response inhibitors. 网络驱动的癌细胞化身，用于 DNA 损伤反应抑制剂的组合发现和生物标记物鉴定。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-21 DOI: 10.1038/s41540-024-00394-w

Orsolya Papp, Viktória Jordán, Szabolcs Hetey, Róbert Balázs, Valér Kaszás, Árpád Bartha, Nóra N Ordasi, Sebestyén Kamp, Bálint Farkas, Jerome Mettetal, Jonathan R Dry, Duncan Young, Ben Sidders, Krishna C Bulusu, Daniel V Veres

{"title":"Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA damage response inhibitors.","authors":"Orsolya Papp, Viktória Jordán, Szabolcs Hetey, Róbert Balázs, Valér Kaszás, Árpád Bartha, Nóra N Ordasi, Sebestyén Kamp, Bálint Farkas, Jerome Mettetal, Jonathan R Dry, Duncan Young, Ben Sidders, Krishna C Bulusu, Daniel V Veres","doi":"10.1038/s41540-024-00394-w","DOIUrl":"10.1038/s41540-024-00394-w","url":null,"abstract":"Combination therapy is well established as a key intervention strategy for cancer treatment, with the potential to overcome monotherapy resistance and deliver a more durable efficacy. However, given the scale of unexplored potential target space and the resulting combinatorial explosion, identifying efficacious drug combinations is a critical unmet need that is still evolving. In this paper, we demonstrate a network biology-driven, simulation-based solution, the Simulated Cell™. Integration of omics data with a curated signaling network enables the accurate and interpretable prediction of 66,348 combination-cell line pairs obtained from a large-scale combinatorial drug sensitivity screen of 684 combinations across 97 cancer cell lines (BAC = 0.62, AUC = 0.7). We highlight drug combination pairs that interact with DNA Damage Response pathways and are predicted to be synergistic, and deep network insight to identify biomarkers driving combination synergy. We demonstrate that the cancer cell 'avatars' capture the biological complexity of their in vitro counterparts, enabling the identification of pathway-level mechanisms of combination benefit to guide clinical translatability.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11192759/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141437264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Canalization reduces the nonlinearity of regulation in biological networks. 渠化降低了生物网络调节的非线性。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-13 DOI: 10.1038/s41540-024-00392-y

Claus Kadelka, David Murrugarra

{"title":"Canalization reduces the nonlinearity of regulation in biological networks.","authors":"Claus Kadelka, David Murrugarra","doi":"10.1038/s41540-024-00392-y","DOIUrl":"10.1038/s41540-024-00392-y","url":null,"abstract":"Biological networks, such as gene regulatory networks, possess desirable properties. They are more robust and controllable than random networks. This motivates the search for structural and dynamical features that evolution has incorporated into biological networks. A recent meta-analysis of published, expert-curated Boolean biological network models has revealed several such features, often referred to as design principles. Among others, the biological networks are enriched for certain recurring network motifs, the dynamic update rules are more redundant, more biased, and more canalizing than expected, and the dynamics of biological networks are better approximable by linear and lower-order approximations than those of comparable random networks. Since most of these features are interrelated, it is paramount to disentangle cause and effect, that is, to understand which features evolution actively selects for, and thus truly constitute evolutionary design principles. Here, we compare published Boolean biological network models with different ensembles of null models and show that the abundance of canalization in biological networks can almost completely explain their recently postulated high approximability. Moreover, an analysis of random N-K Kauffman models reveals a strong dependence of approximability on the dynamical robustness of a network.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11176187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141317923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

interFLOW: maximum flow framework for the identification of factors mediating the signaling convergence of multiple receptors. interFLOW：用于识别介导多种受体信号汇聚的因素的最大流量框架。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-10 DOI: 10.1038/s41540-024-00391-z

Ron Sheinin, Koren Salomon, Eilam Yeini, Shai Dulberg, Ayelet Kaminitz, Ronit Satchi-Fainaro, Roded Sharan, Asaf Madi

{"title":"interFLOW: maximum flow framework for the identification of factors mediating the signaling convergence of multiple receptors.","authors":"Ron Sheinin, Koren Salomon, Eilam Yeini, Shai Dulberg, Ayelet Kaminitz, Ronit Satchi-Fainaro, Roded Sharan, Asaf Madi","doi":"10.1038/s41540-024-00391-z","DOIUrl":"10.1038/s41540-024-00391-z","url":null,"abstract":"Cell-cell crosstalk involves simultaneous interactions of multiple receptors and ligands, followed by downstream signaling cascades working through receptors converging at dominant transcription factors, which then integrate and propagate multiple signals into a cellular response. Single-cell RNAseq of multiple cell subsets isolated from a defined microenvironment provides us with a unique opportunity to learn about such interactions reflected in their gene expression levels. We developed the interFLOW framework to map the potential ligand-receptor interactions between different cell subsets based on a maximum flow computation in a network of protein-protein interactions (PPIs). The maximum flow approach further allows characterization of the intracellular downstream signal transduction from differentially expressed receptors towards dominant transcription factors, therefore, enabling the association between a set of receptors and their downstream activated pathways. Importantly, we were able to identify key transcription factors toward which the convergence of multiple receptor signaling pathways occurs. These identified factors have a unique role in the integration and propagation of signaling following specific cell-cell interactions.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11164912/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141301140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events. 低频 ERK 和 Akt 活性动态可预测随机细胞分裂事件。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-04 DOI: 10.1038/s41540-024-00389-7

Jamie J R Bennett, Alan D Stern, Xiang Zhang, Marc R Birtwistle, Gaurav Pandey

{"title":"Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events.","authors":"Jamie J R Bennett, Alan D Stern, Xiang Zhang, Marc R Birtwistle, Gaurav Pandey","doi":"10.1038/s41540-024-00389-7","DOIUrl":"10.1038/s41540-024-00389-7","url":null,"abstract":"Understanding the dynamics of intracellular signaling pathways, such as ERK1/2 (ERK) and Akt1/2 (Akt), in the context of cell fate decisions is important for advancing our knowledge of cellular processes and diseases, particularly cancer. While previous studies have established associations between ERK and Akt activities and proliferative cell fate, the heterogeneity of single-cell responses adds complexity to this understanding. This study employed a data-driven approach to address this challenge, developing machine learning models trained on a dataset of growth factor-induced ERK and Akt activity time courses in single cells, to predict cell division events. The most predictive models were developed by applying discrete wavelet transforms (DWTs) to extract low-frequency features from the time courses, followed by using Ensemble Integration, a data integration and predictive modeling framework. The results demonstrated that these models effectively predicted cell division events in MCF10A cells (F-measure=0.524, AUC=0.726). ERK dynamics were found to be more predictive than Akt, but the combination of both measurements further enhanced predictive performance. The ERK model`s performance also generalized to predicting division events in RPE cells, indicating the potential applicability of these models and our data-driven methodology for predicting cell division across different biological contexts. Interpretation of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate decisions, and highlights the potential of machine learning approaches in unraveling complex cellular behaviors.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11150372/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141248354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-omics reveals new links between Fructosamine-3-Kinase (FN3K) and core metabolic pathways. 多组学揭示了果糖胺-3-激酶（FN3K）与核心代谢途径之间的新联系。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-03 DOI: 10.1038/s41540-024-00390-0

Safal Shrestha, Rahil Taujale, Samiksha Katiyar, Natarajan Kannan

{"title":"Multi-omics reveals new links between Fructosamine-3-Kinase (FN3K) and core metabolic pathways.","authors":"Safal Shrestha, Rahil Taujale, Samiksha Katiyar, Natarajan Kannan","doi":"10.1038/s41540-024-00390-0","DOIUrl":"10.1038/s41540-024-00390-0","url":null,"abstract":"Fructosamine-3-kinases (FN3Ks) are a conserved family of repair enzymes that phosphorylate reactive sugars attached to lysine residues in peptides and proteins. Although FN3Ks are present across the Tree of Life and share detectable sequence similarity to eukaryotic protein kinases, the biological processes regulated by these kinases are largely unknown. To address this knowledge gap, we leveraged the FN3K CRISPR Knock-Out (KO) HepG2 cell line alongside an integrative multi-omics study combining transcriptomics, metabolomics, and interactomics to place these enzymes in a pathway context. The integrative analyses revealed the enrichment of pathways related to oxidative stress response, lipid biosynthesis (cholesterol and fatty acids), and carbon and co-factor metabolism. Moreover, enrichment of nicotinamide adenine dinucleotide (NAD) binding proteins and localization of human FN3K (HsFN3K) to mitochondria suggests potential links between FN3K and NAD-mediated energy metabolism and redox balance. We report specific binding of HsFN3K to NAD compounds in a metal and concentration-dependent manner and provide insight into their binding mode using modeling and experimental site-directed mutagenesis. Our studies provide a framework for targeting these understudied kinases in diabetic complications and metabolic disorders where redox balance and NAD-dependent metabolic processes are altered.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141238268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrated omics of Saccharomyces cerevisiae CENPK2-1C reveals pleiotropic drug resistance and lipidomic adaptations to cannabidiol. 酿酒酵母 CENPK2-1C 的综合全局分析揭示了对大麻二酚的多向性耐药性和脂质体适应性。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-31 DOI: 10.1038/s41540-024-00382-0

Erin Noel Jordan, Ramin Shirali Hossein Zade, Stephanie Pillay, Paul van Lent, Thomas Abeel, Oliver Kayser

{"title":"Integrated omics of Saccharomyces cerevisiae CENPK2-1C reveals pleiotropic drug resistance and lipidomic adaptations to cannabidiol.","authors":"Erin Noel Jordan, Ramin Shirali Hossein Zade, Stephanie Pillay, Paul van Lent, Thomas Abeel, Oliver Kayser","doi":"10.1038/s41540-024-00382-0","DOIUrl":"10.1038/s41540-024-00382-0","url":null,"abstract":"Yeast metabolism can be engineered to produce xenobiotic compounds, such as cannabinoids, the principal isoprenoids of the plant Cannabis sativa, through heterologous metabolic pathways. However, yeast cell factories continue to have low cannabinoid production. This study employed an integrated omics approach to investigate the physiological effects of cannabidiol on S. cerevisiae CENPK2-1C yeast cultures. We treated the experimental group with 0.5 mM CBD and monitored CENPK2-1C cultures. We observed a latent-stationary phase post-diauxic shift in the experimental group and harvested samples in the inflection point of this growth phase for transcriptomic and metabolomic analysis. We compared the transcriptomes of the CBD-treated yeast and the positive control, identifying eight significantly overexpressed genes with a log fold change of at least 1.5 and a significant adjusted p-value. Three notable genes were PDR5 (an ABC-steroid and cation transporter), CIS1, and YGR035C. These genes are all regulated by pleiotropic drug resistance linked promoters. Knockout and rescue of PDR5 showed that it is a causal factor in the post-diauxic shift phenotype. Metabolomic analysis revealed 48 significant spectra associated with CBD-fed cell pellets, 20 of which were identifiable as non-CBD compounds, including fatty acids, glycerophospholipids, and phosphate-salvage indicators. Our results suggest that mitochondrial regulation and lipidomic remodeling play a role in yeast's response to CBD, which are employed in tandem with pleiotropic drug resistance (PDR). We conclude that bioengineers should account for off-target product C-flux, energy use from ABC-transport, and post-stationary phase cell growth when developing cannabinoid-biosynthetic yeast strains.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11143246/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141183603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles. 通过预测扰乱基因表达谱的染色质可及性变化来识别药物反应增强子。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-30 DOI: 10.1038/s41540-024-00388-8

Yongcui Wang, Yong Wang

{"title":"Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles.","authors":"Yongcui Wang, Yong Wang","doi":"10.1038/s41540-024-00388-8","DOIUrl":"10.1038/s41540-024-00388-8","url":null,"abstract":"Individual may response to drug treatment differently due to their genetic variants located in enhancers. These variants can alter transcription factor's (TF) binding strength, affect enhancer's chromatin activity or interaction, and eventually change expression level of downstream gene. Here, we propose a computational framework, PERD, to Predict the Enhancers Responsive to Drug. A machine learning model was trained to predict the genome-wide chromatin accessibility from transcriptome data using the paired expression and chromatin accessibility data collected from ENCODE and ROADMAP. Then the model was applied to the perturbed gene expression data from Connectivity Map (CMAP) and Cancer Drug-induced gene expression Signature DataBase (CDS-DB) and identify drug responsive enhancers with significantly altered chromatin accessibility. Furthermore, the drug responsive enhancers were related to the pharmacogenomics genome-wide association studies (PGx GWAS). Stepping on the traditional drug-associated gene signatures, PERD holds the promise to enhance the causality of drug perturbation by providing candidate regulatory element of those drug associated genes.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11139989/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141179312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The art of modeling gene regulatory circuits. 基因调控回路建模艺术。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-29 DOI: 10.1038/s41540-024-00380-2

Mariana Gómez-Schiavon, Isabel Montejano-Montelongo, F Sophia Orozco-Ruiz, Cristina Sotomayor-Vivas

引用次数: 0