NPJ Systems Biology and Applications最新文献_第3页

Author Correction: Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA damage response inhibitors. 作者更正：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志物鉴定。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-08-08 DOI: 10.1038/s41540-024-00416-7

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

引用次数: 0

Modelling HIV-1 control and remission. 模拟 HIV-1 的控制和缓解。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-08-08 DOI: 10.1038/s41540-024-00407-8

Bharadwaj Vemparala, Shreya Chowdhury, Jérémie Guedj, Narendra M Dixit

引用次数: 0

On the salient limitations of the methods of assembly theory and their classification of molecular biosignatures. 关于组装理论及其分子生物特征分类方法的突出局限性。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-08-07 DOI: 10.1038/s41540-024-00403-y

Abicumaran Uthamacumaran, Felipe S Abrahão, Narsis A Kiani, Hector Zenil

引用次数: 0

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data. 在多队列多组学数据上使用生物可解释神经网络进行表型预测。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-08-02 DOI: 10.1038/s41540-024-00405-w

Arno van Hilten, Jeroen van Rooij, M Arfan Ikram, Wiro J Niessen, Joyce B J van Meurs, Gennady V Roshchupkin

{"title":"Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data.","authors":"Arno van Hilten, Jeroen van Rooij, M Arfan Ikram, Wiro J Niessen, Joyce B J van Meurs, Gennady V Roshchupkin","doi":"10.1038/s41540-024-00405-w","DOIUrl":"10.1038/s41540-024-00405-w","url":null,"abstract":"Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is essential for precision medicine. In this study, we developed interpretable predictive models for multi-omics data by employing neural networks informed by prior biological knowledge, referred to as visible networks. These neural networks offer insights into the decision-making process and can unveil novel perspectives on the underlying biological mechanisms associated with traits and complex diseases. We tested the performance, interpretability and generalizability for inferring smoking status, subject age and LDL levels using genome-wide RNA expression and CpG methylation data from the blood of the BIOS consortium (four population cohorts, Ntotal = 2940). In a cohort-wise cross-validation setting, the consistency of the diagnostic performance and interpretation was assessed. Performance was consistently high for predicting smoking status with an overall mean AUC of 0.95 (95% CI: 0.90-1.00) and interpretation revealed the involvement of well-replicated genes such as AHRR, GPR15 and LRRN3. LDL-level predictions were only generalized in a single cohort with an R2 of 0.07 (95% CI: 0.05-0.08). Age was inferred with a mean error of 5.16 (95% CI: 3.97-6.35) years with the genes COL11A2, AFAP1, OTUD7A, PTPRN2, ADARB2 and CD34 consistently predictive. For both regression tasks, we found that using multi-omics networks improved performance, stability and generalizability compared to interpretable single omic networks. We believe that visible neural networks have great potential for multi-omics analysis; they combine multi-omic data elegantly, are interpretable, and generalize well to data from different cohorts.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11297229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141879208","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

Bifurcations in coupled amyloid-β aggregation-inflammation systems. 淀粉样蛋白-β聚集-炎症耦合系统中的分岔。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-30 DOI: 10.1038/s41540-024-00408-7

Kalyan S Chakrabarti, Davood Bakhtiari, Nasrollah Rezaei-Ghaleh

{"title":"Bifurcations in coupled amyloid-β aggregation-inflammation systems.","authors":"Kalyan S Chakrabarti, Davood Bakhtiari, Nasrollah Rezaei-Ghaleh","doi":"10.1038/s41540-024-00408-7","DOIUrl":"10.1038/s41540-024-00408-7","url":null,"abstract":"A complex interplay between various processes underlies the neuropathology of Alzheimer's disease (AD) and its progressive course. Several lines of evidence point to the coupling between Aβ aggregation and neuroinflammation and its role in maintaining brain homeostasis during the long prodromal phase of AD. Little is however known about how this protective mechanism fails and as a result, an irreversible and progressive transition to clinical AD occurs. Here, we introduce a minimal model of a coupled system of Aβ aggregation and inflammation, numerically simulate its dynamical behavior, and analyze its bifurcation properties. The introduced model represents the following events: generation of Aβ monomers, aggregation of Aβ monomers into oligomers and fibrils, induction of inflammation by Aβ aggregates, and clearance of various Aβ species. Crucially, the rates of Aβ generation and clearance are modulated by inflammation level following a Hill-type response function. Despite its relative simplicity, the model exhibits enormously rich dynamics ranging from overdamped kinetics to sustained oscillations. We then specify the region of inflammation- and coupling-related parameters space where a transition to oscillatory dynamics occurs and demonstrate how changes in Aβ aggregation parameters could shift this oscillatory region in parameter space. Our results reveal the propensity of coupled Aβ aggregation-inflammation systems to oscillatory dynamics and propose prolonged sustained oscillations and their consequent immune system exhaustion as a potential mechanism underlying the transition to a more progressive phase of amyloid pathology in AD. The implications of our results in regard to early diagnosis of AD and anti-AD drug development are discussed.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11289389/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141856128","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

A possible path to persistent re-entry waves at the outlet of the left pulmonary vein. 左肺静脉出口处出现持续性再入波的可能途径。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-23 DOI: 10.1038/s41540-024-00406-9

Karoline Horgmo Jæger, Aslak Tveito

{"title":"A possible path to persistent re-entry waves at the outlet of the left pulmonary vein.","authors":"Karoline Horgmo Jæger, Aslak Tveito","doi":"10.1038/s41540-024-00406-9","DOIUrl":"10.1038/s41540-024-00406-9","url":null,"abstract":"Atrial fibrillation (AF) is the most common form of cardiac arrhythmia, often evolving from paroxysmal episodes to persistent stages over an extended timeframe. While various factors contribute to this progression, the precise biophysical mechanisms driving it remain unclear. Here we explore how rapid firing of cardiomyocytes at the outlet of the pulmonary vein of the left atria can create a substrate for a persistent re-entry wave. This is grounded in a recently formulated mathematical model of the regulation of calcium ion channel density by intracellular calcium concentration. According to the model, the number of calcium channels is controlled by the intracellular calcium concentration. In particular, if the concentration increases above a certain target level, the calcium current is weakened to restore the target level of calcium. During rapid pacing, the intracellular calcium concentration of the cardiomyocytes increases leading to a substantial reduction of the calcium current across the membrane of the myocytes, which again reduces the action potential duration. In a spatially resolved cell-based model of the outlet of the pulmonary vein of the left atria, we show that the reduced action potential duration can lead to re-entry. Initiated by rapid pacing, often stemming from paroxysmal AF episodes lasting several days, the reduction in calcium current is a critical factor. Our findings illustrate how such episodes can foster a conducive environment for persistent AF through electrical remodeling, characterized by diminished calcium currents. This underscores the importance of promptly addressing early AF episodes to prevent their progression to chronic stages.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11266599/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141752276","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

Self-consistent signal transduction analysis for modeling context-specific signaling cascades and perturbations. 自洽信号转导分析，用于模拟特定环境下的信号级联和扰动。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-19 DOI: 10.1038/s41540-024-00404-x

John Cole

引用次数: 0

Including glutamine in a resource allocation model of energy metabolism in cancer and yeast cells. 将谷氨酰胺纳入癌细胞和酵母细胞能量代谢的资源分配模型。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-18 DOI: 10.1038/s41540-024-00393-x

Jan Ewald, Ziyang He, Wassili Dimitriew, Stefan Schuster

{"title":"Including glutamine in a resource allocation model of energy metabolism in cancer and yeast cells.","authors":"Jan Ewald, Ziyang He, Wassili Dimitriew, Stefan Schuster","doi":"10.1038/s41540-024-00393-x","DOIUrl":"10.1038/s41540-024-00393-x","url":null,"abstract":"Energy metabolism is crucial for all living cells, especially during fast growth or stress scenarios. Many cancer and activated immune cells (Warburg effect) or yeasts (Crabtree effect) mostly rely on aerobic glucose fermentation leading to lactate or ethanol, respectively, to generate ATP. In recent years, several mathematical models have been proposed to explain the Warburg effect on theoretical grounds. Besides glucose, glutamine is a very important substrate for eukaryotic cells-not only for biosynthesis, but also for energy metabolism. Here, we present a minimal constraint-based stoichiometric model for explaining both the classical Warburg effect and the experimentally observed respirofermentation of glutamine (WarburQ effect). We consider glucose and glutamine respiration as well as the respective fermentation pathways. Our resource allocation model calculates the ATP production rate, taking into account enzyme masses and, therefore, pathway costs. While our calculation predicts glucose fermentation to be a superior energy-generating pathway in human cells, different enzyme characteristics in yeasts reduce this advantage, in some cases to such an extent that glucose respiration is preferred. The latter is observed for the fungal pathogen Candida albicans, which is a known Crabtree-negative yeast. Further, optimization results show that glutamine is a valuable energy source and important substrate under glucose limitation, in addition to its role as a carbon and nitrogen source of biomass in eukaryotic cells. In conclusion, our model provides insights that glutamine is an underestimated fuel for eukaryotic cells during fast growth and infection scenarios and explains well the observed parallel respirofermentation of glucose and glutamine in several cell types.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11258256/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141724077","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

A deep position-encoding model for predicting olfactory perception from molecular structures and electrostatics. 从分子结构和静电学预测嗅觉感知的深度位置编码模型。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-17 DOI: 10.1038/s41540-024-00401-0

Mengji Zhang, Yusuke Hiki, Akira Funahashi, Tetsuya J Kobayashi

{"title":"A deep position-encoding model for predicting olfactory perception from molecular structures and electrostatics.","authors":"Mengji Zhang, Yusuke Hiki, Akira Funahashi, Tetsuya J Kobayashi","doi":"10.1038/s41540-024-00401-0","DOIUrl":"10.1038/s41540-024-00401-0","url":null,"abstract":"Predicting olfactory perceptions from odorant molecules is challenging due to the complex and potentially discontinuous nature of the perceptual space for smells. In this study, we introduce a deep learning model, Mol-PECO (Molecular Representation by Positional Encoding of Coulomb Matrix), designed to predict olfactory perceptions based on molecular structures and electrostatics. Mol-PECO learns the efficient embedding of molecules by utilizing the Coulomb matrix, which encodes atomic coordinates and charges, as an alternative of the adjacency matrix and its Laplacian eigenfunctions as positional encoding of atoms. With a comprehensive dataset of odor molecules and descriptors, Mol-PECO outperforms traditional machine learning methods using molecular fingerprints and graph neural networks based on adjacency matrices. The learned embeddings by Mol-PECO effectively capture the odor space, enabling global clustering of descriptors and local retrieval of similar odorants. This work contributes to a deeper understanding of the olfactory sense and its mechanisms.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11255234/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634123","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

Systems modeling of oncogenic G-protein and GPCR signaling reveals unexpected differences in downstream pathway activation. 致癌 G 蛋白和 GPCR 信号的系统建模揭示了下游通路激活中意想不到的差异。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-16 DOI: 10.1038/s41540-024-00400-1

Michael Trogdon, Kodye Abbott, Nadia Arang, Kathryn Lande, Navneet Kaur, Melinda Tong, Mathieu Bakhoum, J Silvio Gutkind, Edward C Stites

{"title":"Systems modeling of oncogenic G-protein and GPCR signaling reveals unexpected differences in downstream pathway activation.","authors":"Michael Trogdon, Kodye Abbott, Nadia Arang, Kathryn Lande, Navneet Kaur, Melinda Tong, Mathieu Bakhoum, J Silvio Gutkind, Edward C Stites","doi":"10.1038/s41540-024-00400-1","DOIUrl":"10.1038/s41540-024-00400-1","url":null,"abstract":"Mathematical models of biochemical reaction networks are an important and emerging tool for the study of cell signaling networks involved in disease processes. One promising potential application of such mathematical models is the study of how disease-causing mutations promote the signaling phenotype that contributes to the disease. It is commonly assumed that one must have a thorough characterization of the network readily available for mathematical modeling to be useful, but we hypothesized that mathematical modeling could be useful when there is incomplete knowledge and that it could be a tool for discovery that opens new areas for further exploration. In the present study, we first develop a mechanistic mathematical model of a G-protein coupled receptor signaling network that is mutated in almost all cases of uveal melanoma and use model-driven explorations to uncover and explore multiple new areas for investigating this disease. Modeling the two major, mutually-exclusive, oncogenic mutations (Gαq/11 and CysLT2R) revealed the potential for previously unknown qualitative differences between seemingly interchangeable disease-promoting mutations, and our experiments confirmed oncogenic CysLT2R was impaired at activating the FAK/YAP/TAZ pathway relative to Gαq/11. This led us to hypothesize that CYSLTR2 mutations in UM must co-occur with other mutations to activate FAK/YAP/TAZ signaling, and our bioinformatic analysis uncovers a role for co-occurring mutations involving the plexin/semaphorin pathway, which has been shown capable of activating this pathway. Overall, this work highlights the power of mechanism-based computational systems biology as a discovery tool that can leverage available information to open new research areas.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11252164/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141627232","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