Article
Biochemical Research Methods
Zhen Gao, Jin Tang, Junfeng Xia, Chun-Hou Zheng, Pi-Jing Wei
Summary: This study proposes a supervised model called CNNGRN, which uses a convolutional neural network to reconstruct gene regulatory networks from gene expression data. The model integrates gene expression data and network structure information, and uses the extracted complex features to infer regulatory relationships. Experimental results show that CNNGRN achieves competitive performance on benchmark datasets and confirms key genes involved in biological processes.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Biotechnology & Applied Microbiology
Wenqing Jiang, Roby Joehanes, Daniel Levy, George T. O'Connor, Josee Dupuis
Summary: In this study, a novel approach was developed to improve clustering of gene expression by integrating regulatory data from different but partially overlapping sets of individuals.
Article
Oncology
Yanglan Gan, Xin Hu, Guobing Zou, Cairong Yan, Guangwei Xu
Summary: The article introduces a new computational algorithm BiRGRN for inferring gene regulatory networks (GRNs) from time-series single-cell RNA-seq data. The algorithm utilizes a bidirectional recurrent neural network to transform the inference of GRNs into a regression problem, and adopts bidirectional structure and prior knowledge filtering strategy to improve accuracy and stability.
FRONTIERS IN ONCOLOGY
(2022)
Article
Biochemical Research Methods
Neel Patel, William S. Bush
Summary: This study developed a general model of transcription factor influence on gene expression by incorporating both cis and trans gene regulatory features. The models performed significantly better compared to models containing only cis-regulatory features, and the inclusion of long distance chromatin interactions further improved accuracy. The refined effect estimates generated by the models allow for characterization of individual transcription factors' roles across the genome, providing a framework for integrating multiple data types into a single model of transcriptional regulation.
BMC BIOINFORMATICS
(2021)
Article
Biology
Yanglan Gan, Yongchang Xin, Xin Hu, Guobing Zou
Summary: Gene regulatory network models the interactions between transcription factors and target genes, and is crucial for understanding gene function. iMPRN, a computational method integrating multiple prior networks, can accurately infer and optimize regulatory networks leading to key insights into gene regulation.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2021)
Article
Biochemistry & Molecular Biology
Vijaykumar Yogesh Muley, Rainer Koenig
Summary: This study compares transcriptional regulatory pairs from multiple databases and finds that TF and TG are common across data resources, but their regulatory pairs are not. The regulatory pairs show weak expression correlation, but significant gene ontology overlap and co-citations in PubMed, with a small number of TF-TG pairs representing transcriptional repression relationships. The assembled TRN provides a valuable resource for benchmarking TRN prediction tools and for researchers in functional genomics, gene expression, and regulation analysis.
Article
Plant Sciences
Xiaokun Wang, Xianglan Wang, Shilei Sun, Xiaoyu Tu, Kande Lin, Lei Qin, Xingyun Wang, Gang Li, Silin Zhong, Pinghua Li
Summary: Various regulatory modules control leaf angle in maize. In this study, the transcription factor ZmBEH1 was found to regulate leaf angle formation by influencing sclerenchyma cell layers on the adaxial side. ZmBEH1 also interacts with the TF ZmBZR1 and ZmSCL28, contributing to the regulation of leaf angle.
Article
Biology
Atefeh Naseri, Mehran Sharghi, Seyed Mohammad Hossein Hasheminejad
Summary: The study introduces an enhanced diffusion-based method for integrating various types of biological data to reconstruct gene regulatory networks, resulting in an improvement of 0.02-0.08 units in AUROC criteria across different research methods.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2021)
Article
Computer Science, Information Systems
Chuanyuan Wang, Shiyu Xu, Zhi-Ping Liu
Summary: This study proposes a framework called Network Activity Evaluation (NAE) that evaluates the activity of gene regulatory events by measuring the consistency between gene expression data and network structure. The efficiency and advantages of the NAE framework are demonstrated through multiple experiments and comparison studies.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Review
Biochemical Research Methods
Mengyuan Zhao, Wenying He, Jijun Tang, Quan Zou, Fei Guo
Summary: The study focuses on the importance of GRN reconstruction technologies in biology and medical science, discussing different method classifications and their performance in networks of varying scales. The aim is to discover potential drug targets and identify cancer biomarkers.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Ana Carolina Leote, Xiaohui Wu, Andreas Beyer
Summary: Single-cell RNA sequencing methods often cannot accurately quantify the expression levels of all genes in a cell. In this study, we propose a network-based approach for dropout imputation, which utilizes gene-gene relationship information from external datasets. Our approach outperforms existing methods in various human scRNA-seq datasets, especially for lowly expressed genes. We also find that some genes cannot be adequately imputed by any method tested. Based on our findings, we developed an R-package called ADImpute that automatically determines the best imputation method for each gene in a dataset.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Genetics & Heredity
Pauline Schmitt, Baptiste Sorin, Timothee Froute, Nicolas Parisot, Federica Calevro, Sergio Peignier
Summary: This research introduces GReNaDIne, a Python package that implements 18 machine learning data-driven gene regulatory network inference methods. It also includes preprocessing techniques suitable for both RNA-seq and microarray dataset analysis, as well as normalization techniques dedicated to RNA-seq. In addition, it allows for combining the results of different inference tools to form robust ensembles. The package has been successfully evaluated under the DREAM5 challenge benchmark dataset.
Review
Engineering, Chemical
Seong Beom Cho
Summary: This review introduces various methods for inferring gene regulatory networks in cancer research, including pair-wise measures, multivariate measures, and supervised integrative approaches. Most methods are not specifically designed for cancer transcriptome data, indicating the need for a better understanding of cancer pathophysiology and the development of more systematic validation methods in the context of cancer biology.
Article
Biochemical Research Methods
Hantao Shu, Fan Ding, Jingtian Zhou, Yexiang Xue, Dan Zhao, Jianyang Zeng, Jianzhu Ma
Summary: In this study, a weakly supervised learning framework based on the axial transformer was constructed to infer cell-type-specific gene regulatory networks (GRNs) from both single-cell RNA sequencing data and a generic GRN derived from bulk cells. The assumption that bulk-cell transcriptomic data can improve the prediction of single-cell GRNs was verified through extensive experiments, and the proposed GRN-transformer achieved state-of-the-art prediction accuracy.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Juan D. Henao, Michael Lauber, Manuel Azevedo, Anastasiia Grekova, Fabian Theis, Markus List, Christoph Ogris, Benjamin Schubert
Summary: This study integrated regression-based methods that can handle missingness into KiMONo, and benchmarked their performance on commonly encountered missing data scenarios in single- and multi-omics studies. The results showed that two-step approaches that explicitly handle missingness performed best for imbalanced omics-layers dimensions, while methods implicitly handling missingness performed best for balanced omics-layers dimensions. The study demonstrated the feasibility of robust multi-omics network inference in the presence of missing data with KiMONo.
BRIEFINGS IN BIOINFORMATICS
(2023)
Review
Cell Biology
Alyssa Kearly, Andrew D. L. Nelson, Aleksandra Skirycz, Monika Chodasiewicz
Summary: Stress Granules (SGs) and Processing-bodies (P-bodies) are important biomolecular condensates that play crucial roles in maintaining mRNA balance and regulating stress responses. They are composed of proteins and RNAs involved in translation, protein folding, and energy metabolism.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
P. Lemonnier, T. Lawson
Summary: Stomatal conductance plays a crucial role in determining CO2 uptake and water loss in plants, affecting overall water status and productivity. However, the signals coordinating mesophyll demands for CO2, the role of chloroplasts in stomatal function, and other GC metabolic processes in stomatal function remain poorly understood.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Matteo Gionfriddo, Timothy Rhodes, Spencer M. Whitney
Summary: Rubisco is a key enzyme that facilitates the entry of CO2 into the biosphere, but its catalytic properties are slow and error-prone. More effective Rubisco variants have been discovered in certain algae, offering the potential to significantly improve crop productivity. However, incompatibilities in protein folding have hindered the transplantation of these variants into plants. Directed evolution is now being explored to enhance Rubisco catalysis.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Vittoria Clapero, Stephanie Arrivault, Mark Stitt
Summary: The Calvin-Benson cycle has undergone massive selection and co-evolution with carbon-concentrating mechanisms due to changing environmental factors. Metabolite profiling reveals species-specific variations in the operation of the cycle, indicating the influence of different modes of photosynthesis. Connectivity analysis identifies constraints and driving factors for cross-species diversity in the cycle.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Sukhbir Kaur, David D. Roberts
Summary: Thrombospondin-1 modulates cell behavior by interacting with components of the extracellular matrix and cell surface receptors. Its release and expression are influenced by injuries and various diseases, while its sustained presence in the extracellular space is regulated by receptor-mediated clearance. Thrombospondin-1 plays important roles in immune responses.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Richard P. Tucker, Josephine C. Adams
Summary: Thrombospondins (TSPs) play diverse roles in animals and have been found to belong to a superfamily that includes different subgroups such as mega-TSPs, sushi-TSPs, and poriferan-TSPs. Invertebrates encode a greater diversity of TSP superfamily members than vertebrates.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
James Petrik, Sylvia Lauks, Bianca Garlisi, Jack Lawler
Summary: Many cancers start with a small nest of transformed cells that can remain dormant. Thrombospondin-1 (TSP-1) initially promotes dormancy by suppressing angiogenesis, but over time, factors promoting angiogenesis become dominant and recruit various cells to form a complex tumor microenvironment. TSPs play a role in the proliferation, migration, and invasion of cells in the tumor microenvironment, as well as influencing the immune characteristics and phenotype of tumor-associated macrophages.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Hana Fakim, Christine Vande Velde
Summary: There has been increasing attention to the role of phase-separated biomolecular condensates, specifically stress granules, in neurodegenerative diseases like ALS. ALS-associated mutations in genes involved in stress granule assembly have been found, and stress granule proteins have been detected in pathological inclusions in ALS patient neurons. However, protein components of stress granules are also present in other physiological biomolecular condensates, which have not been adequately discussed in relation to ALS. This review explores the functions of TDP-43 and FUS in physiological condensates occurring in the nucleus and neurites beyond stress granules, and discusses the impact of ALS-linked mutations on their ability to phase separate and perform their functions in stress-independent biomolecular condensates.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Alexander Lin, Yogambha Ramaswamy, Ashish Misra
Summary: Smooth muscle cells, endothelial cells, and macrophages in blood vessels display remarkable heterogeneity, and their developmental origins may influence their plasticity. Unbiased single cell whole transcriptome analysis techniques are revolutionizing the understanding of cellular diversity and plasticity, providing insights for therapeutic research.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Elton P. Hudson
Summary: The Calvin Benson cycle plays a crucial role in the ecological and biotechnological aspects of bacteria. Recent studies have shed light on the regulation of this cycle in bacteria, with post-transcriptional and post-translational regulation being important in phototrophic bacteria, and transcriptional regulation being prominent in chemolithoautotrophic bacteria. Understanding the regulation of the Calvin Benson cycle has implications for enhancing CO2 fixation and improving the synthesis of desired products. Non-canonical cycles may offer potential benefits for industrial applications.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Xin-Guang Zhu, Haim Treves, Honglong Zhao
Summary: This paper discusses the major regulatory mechanisms over the Calvin Benson Cycle (CBC) that maintain homeostasis of metabolite levels. These mechanisms include redox regulation of enzymes, metabolite regulations (especially allosteric regulations), and balanced activities of enzymes. These regulatory mechanisms are crucial for maintaining high flux and photosynthetic efficiency in CBC.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Hunter C. Herriage, Yi-Ting Huang, Brian R. Calvi
Summary: Apoptosis prevents the inappropriate acquisition of extra copies of the genome, known as polyploidy, but the polyploid state can suppress apoptosis. The mechanisms linking apoptosis and polyploid cell cycles are still largely unknown, and studying the regulation of apoptosis in development and cancer could lead to more effective therapies.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Daniel Campbell, Steven Zuryn
Summary: Mitochondrial dynamics play a crucial role in regulating cellular and organismal homeostasis, impacting various aspects of an organism's healthspan. By studying the nematode Caenorhabditis elegans, a comprehensive understanding of the impact of mitochondrial dynamics on homeostasis over a lifetime can be obtained.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Diba Borgmann, Henning Fenselau
Summary: Maintaining blood glucose at an appropriate physiological level requires coordination of multiple organs and tissues, with the vagus nerve playing a key role in central control. Recent studies have revealed the cellular identity, neuroanatomical organization, and functional contributions of vagal neurons in the regulation of systemic glucose metabolism. These findings provide new insights into the precise roles of vagal neurons in coordinating glucose levels and offer potential avenues for treating glucose metabolism disorders.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)
Review
Cell Biology
Tatiana C. Coverdell, Stephen B. G. Abbott, John N. Campbell
Summary: In this article, we review how genetic technology and single-cell genomics are revealing the organizational principles of the efferent vagus in unprecedented detail.
SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
(2024)