keyword
https://read.qxmd.com/read/38493346/incorporating-network-diffusion-and-peak-location-information-for-better-single-cell-atac-seq-data-analysis
#1
JOURNAL ARTICLE
Jiating Yu, Jiacheng Leng, Zhichao Hou, Duanchen Sun, Ling-Yun Wu
Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data provided new insights into the understanding of epigenetic heterogeneity and transcriptional regulation. With the increasing abundance of dataset resources, there is an urgent need to extract more useful information through high-quality data analysis methods specifically designed for scATAC-seq. However, analyzing scATAC-seq data poses challenges due to its near binarization, high sparsity and ultra-high dimensionality properties...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493345/deep-reinforcement-learning-identifies-personalized-intermittent-androgen-deprivation-therapy-for-prostate-cancer
#2
JOURNAL ARTICLE
Yitao Lu, Qian Chu, Zhen Li, Mengdi Wang, Robert Gatenby, Qingpeng Zhang
The evolution of drug resistance leads to treatment failure and tumor progression. Intermittent androgen deprivation therapy (IADT) helps responsive cancer cells compete with resistant cancer cells in intratumoral competition. However, conventional IADT is population-based, ignoring the heterogeneity of patients and cancer. Additionally, existing IADT relies on pre-determined thresholds of prostate-specific antigen to pause and resume treatment, which is not optimized for individual patients. To address these challenges, we framed a data-driven method in two steps...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493344/detox-a-pipeline-for-the-detection-of-toxins-in-venomous-organisms
#3
JOURNAL ARTICLE
Allan Ringeval, Sarah Farhat, Alexander Fedosov, Marco Gerdol, Samuele Greco, Lou Mary, Maria Vittoria Modica, Nicolas Puillandre
Venomous organisms have independently evolved the ability to produce toxins 101 times during their evolutionary history, resulting in over 200 000 venomous species. Collectively, these species produce millions of toxins, making them a valuable resource for bioprospecting and understanding the evolutionary mechanisms underlying genetic diversification. RNA-seq is the preferred method for characterizing toxin repertoires, but the analysis of the resulting data remains challenging. While early approaches relied on similarity-based mapping to known toxin databases, recent studies have highlighted the importance of structural features for toxin detection...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493343/benchmarking-multi-omics-integration-algorithms-across-single-cell-rna-and-atac-data
#4
JOURNAL ARTICLE
Chuxi Xiao, Yixin Chen, Qiuchen Meng, Lei Wei, Xuegong Zhang
Recent advancements in single-cell sequencing technologies have generated extensive omics data in various modalities and revolutionized cell research, especially in the single-cell RNA and ATAC data. The joint analysis across scRNA-seq data and scATAC-seq data has paved the way to comprehending the cellular heterogeneity and complex cellular regulatory networks. Multi-omics integration is gaining attention as an important step in joint analysis, and the number of computational tools in this field is growing rapidly...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493342/scencore-leveraging-single-cell-epigenetic-data-to-predict-chromatin-conformation-using-graph-embedding
#5
JOURNAL ARTICLE
Ziheng Duan, Siwei Xu, Shushrruth Sai Srinivasan, Ahyeon Hwang, Che Yu Lee, Feng Yue, Mark Gerstein, Yu Luan, Matthew Girgenti, Jing Zhang
Dynamic compartmentalization of eukaryotic DNA into active and repressed states enables diverse transcriptional programs to arise from a single genetic blueprint, whereas its dysregulation can be strongly linked to a broad spectrum of diseases. While single-cell Hi-C experiments allow for chromosome conformation profiling across many cells, they are still expensive and not widely available for most labs. Here, we propose an alternate approach, scENCORE, to computationally reconstruct chromatin compartments from the more affordable and widely accessible single-cell epigenetic data...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493341/fusionnw-a-potential-clinical-impact-assessment-of-kinases-in-pan-cancer-fusion-gene-network
#6
JOURNAL ARTICLE
Chengyuan Yang, Himansu Kumar, Pora Kim
Kinase fusion genes are the most active fusion gene group in human cancer fusion genes. To help choose the clinically significant kinase so that the cancer patients that have fusion genes can be better diagnosed, we need a metric to infer the assessment of kinases in pan-cancer fusion genes rather than relying on the sample frequency expressed fusion genes. Most of all, multiple studies assessed human kinases as the drug targets using multiple types of genomic and clinical information, but none used the kinase fusion genes in their study...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493340/translational-bioinformatics-and-data-science-for-biomarker-discovery-in-mental-health-an-analytical-review
#7
JOURNAL ARTICLE
Krithika Bhuvaneshwar, Yuriy Gusev
Translational bioinformatics and data science play a crucial role in biomarker discovery as it enables translational research and helps to bridge the gap between the bench research and the bedside clinical applications. Thanks to newer and faster molecular profiling technologies and reducing costs, there are many opportunities for researchers to explore the molecular and physiological mechanisms of diseases. Biomarker discovery enables researchers to better characterize patients, enables early detection and intervention/prevention and predicts treatment responses...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493339/scmlc-an-accurate-and-robust-multiplex-community-detection-method-for-single-cell-multi-omics-data
#8
JOURNAL ARTICLE
Yuxuan Chen, Ruiqing Zheng, Jin Liu, Min Li
Clustering cells based on single-cell multi-modal sequencing technologies provides an unprecedented opportunity to create high-resolution cell atlas, reveal cellular critical states and study health and diseases. However, effectively integrating different sequencing data for cell clustering remains a challenging task. Motivated by the successful application of Louvain in scRNA-seq data, we propose a single-cell multi-modal Louvain clustering framework, called scMLC, to tackle this problem. scMLC builds multiplex single- and cross-modal cell-to-cell networks to capture modal-specific and consistent information between modalities and then adopts a robust multiplex community detection method to obtain the reliable cell clusters...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493338/effective-multi-modal-clustering-method-via-skip-aggregation-network-for-parallel-scrna-seq-and-scatac-seq-data
#9
JOURNAL ARTICLE
Dayu Hu, Ke Liang, Zhibin Dong, Jun Wang, Yawei Zhao, Kunlun He
In recent years, there has been a growing trend in the realm of parallel clustering analysis for single-cell RNA-seq (scRNA) and single-cell Assay of Transposase Accessible Chromatin (scATAC) data. However, prevailing methods often treat these two data modalities as equals, neglecting the fact that the scRNA mode holds significantly richer information compared to the scATAC. This disregard hinders the model benefits from the insights derived from multiple modalities, compromising the overall clustering performance...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493292/the-rise-of-taxon-specific-epitope-predictors
#10
JOURNAL ARTICLE
Felipe Campelo, Francisco P Lobo
Computational predictors of immunogenic peptides, or epitopes, are traditionally built based on data from a broad range of pathogens without consideration for taxonomic information. While this approach may be reasonable if one aims to develop one-size-fits-all models, it may be counterproductive if the proteins for which the model is expected to generalize are known to come from a specific subset of phylogenetically related pathogens. There is mounting evidence that, for these cases, taxon-specific models can outperform generalist ones, even when trained with substantially smaller amounts of data...
January 22, 2024: Briefings in Bioinformatics
https://read.qxmd.com/read/38493218/hoxd3-promotes-the-migration-and-angiogenesis-of-hepatocellular-carcinoma-via-modifying-hepatocellular-carcinoma-cells-exosome-delivered-ccr6-and-regulating-chromatin-conformation-of-ccl20
#11
JOURNAL ARTICLE
Lumin Wang, Chenyang Qiao, Lili Han, Xiaofei Wang, Jiyu Miao, Li Cao, Chen Huang, Jinhai Wang
Angiogenesis plays an essential role in the microenvironment of hepatocellular carcinoma (HCC). HOXD3 is involved in the metastasis and invasion of HCC cells; Whereas the underlying molecular mechanisms in the microenvironment of HCC remain unknown. Wound healing, transwell invasion, tube formation and spheroid sprouting assays were carried out to identify the effects of HCC-HOXD3-exosomes and genes on the migration of HCC cells. ChIP-PCR was applied to test the binding region of HOXD3 on CCR6, Med15, and CREBBP promoter...
March 16, 2024: Cell Death & Disease
https://read.qxmd.com/read/38493179/identification-and-validation-of-irf6-related-to-ovarian-cancer-and-biological-function-and-prognostic-value
#12
JOURNAL ARTICLE
Shihao Hong, Ni Fu, Shanliang Sang, Xudong Ma, Fangying Sun, Xiao Zhang
BACKGROUND: Ovarian cancer (OC) is a severe gynecological malignancy with significant diagnostic and therapeutic challenges. The discovery of reliable cancer biomarkers can be used to adjust diagnosis and improve patient care. However, serous OC lacks effective biomarkers. We aimed to identify novel biomarkers for OC and their pathogenic causes. METHODS: The present study used the differentially expressed genes (DEGs) obtained from the "Limma" package and WGCNA modules for intersection analysis to obtain DEGs in OC...
March 16, 2024: Journal of Ovarian Research
https://read.qxmd.com/read/38493171/rna-editing-enzymes-structure-biological-functions-and-applications
#13
REVIEW
Dejiu Zhang, Lei Zhu, Yanyan Gao, Yin Wang, Peifeng Li
With the advancement of sequencing technologies and bioinformatics, over than 170 different RNA modifications have been identified. However, only a few of these modifications can lead to base pair changes, which are called RNA editing. RNA editing is a ubiquitous modification in mammalian transcriptomes and is an important co/posttranscriptional modification that plays a crucial role in various cellular processes. There are two main types of RNA editing events: adenosine to inosine (A-to-I) editing, catalyzed by ADARs on double-stranded RNA or ADATs on tRNA, and cytosine to uridine (C-to-U) editing catalyzed by APOBECs...
March 16, 2024: Cell & Bioscience
https://read.qxmd.com/read/38493149/casein-kinase-2-phosphorylates-and-induces-the-sall2-tumor-suppressor-degradation-in-colon-cancer-cells
#14
JOURNAL ARTICLE
V E Hermosilla, L Gyenis, A J Rabalski, M E Armijo, P Sepúlveda, F Duprat, D Benítez-Riquelme, F Fuentes-Villalobos, A Quiroz, M I Hepp, C Farkas, M Mastel, I González-Chavarría, R Jackstadt, D W Litchfield, A F Castro, R Pincheira
Spalt-like proteins are Zinc finger transcription factors from Caenorhabditis elegans to vertebrates, with critical roles in development. In vertebrates, four paralogues have been identified (SALL1-4), and SALL2 is the family's most dissimilar member. SALL2 is required during brain and eye development. It is downregulated in cancer and acts as a tumor suppressor, promoting cell cycle arrest and cell death. Despite its critical functions, information about SALL2 regulation is scarce. Public data indicate that SALL2 is ubiquitinated and phosphorylated in several residues along the protein, but the mechanisms, biological consequences, and enzymes responsible for these modifications remain unknown...
March 16, 2024: Cell Death & Disease
https://read.qxmd.com/read/38493130/infrared-a-declarative-tree-decomposition-powered-framework-for-bioinformatics
#15
JOURNAL ARTICLE
Hua-Ting Yao, Bertrand Marchand, Sarah J Berkemer, Yann Ponty, Sebastian Will
MOTIVATION: Many bioinformatics problems can be approached as optimization or controlled sampling tasks, and solved exactly and efficiently using Dynamic Programming (DP). However, such exact methods are typically tailored towards specific settings, complex to develop, and hard to implement and adapt to problem variations. METHODS: We introduce the Infrared framework to overcome such hindrances for a large class of problems. Its underlying paradigm is tailored toward problems that can be declaratively formalized as sparse feature networks, a generalization of constraint networks...
March 16, 2024: Algorithms for Molecular Biology: AMB
https://read.qxmd.com/read/38493120/using-protein-language-models-for-protein-interaction-hot-spot-prediction-with-limited-data
#16
JOURNAL ARTICLE
Karen Sargsyan, Carmay Lim
BACKGROUND: Protein language models, inspired by the success of large language models in deciphering human language, have emerged as powerful tools for unraveling the intricate code of life inscribed within protein sequences. They have gained significant attention for their promising applications across various areas, including the sequence-based prediction of secondary and tertiary protein structure, the discovery of new functional protein sequences/folds, and the assessment of mutational impact on protein fitness...
March 16, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38493095/integration-of-scrna-seq-data-by-disentangled-representation-learning-with-condition-domain-adaptation
#17
JOURNAL ARTICLE
Renjing Liu, Kun Qian, Xinwei He, Hongwei Li
BACKGROUND: The integration of single-cell RNA sequencing data from multiple experimental batches and diverse biological conditions holds significant importance in the study of cellular heterogeneity. RESULTS: To expedite the exploration of systematic disparities under various biological contexts, we propose a scRNA-seq integration method called scDisco, which involves a domain-adaptive decoupling representation learning strategy for the integration of dissimilar single-cell RNA data...
March 16, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38493090/involvement-of-fgf2-mediated-tau-protein-phosphorylation-in-cognitive-deficits-induced-by-sevoflurane-in-aged-rats
#18
JOURNAL ARTICLE
Xin Xie, Xiaomin Zhang, Songze Li, Wei Du
OBJECTIVE: Anesthetics have been linked to cognitive alterations, particularly in the elderly. The current research delineates how Fibroblast Growth Factor 2 (Fgf2) modulates tau protein phosphorylation, contributing to cognitive impairments in aged rats upon sevoflurane administration. METHODS: Rats aged 3, 12, and 18 months were subjected to a 2.5% sevoflurane exposure to form a neurotoxicity model. Cognitive performance was gauged, and the GEO database was employed to identify differentially expressed genes (DEGs) in the 18-month-old cohort post sevoflurane exposure...
March 16, 2024: Molecular Medicine
https://read.qxmd.com/read/38492762/in-vivo-assessment-of-the-toxic-impact-of-exposure-to-magnetic-iron-oxide-nanoparticles-ionps-using-drosophila-melanogaster
#19
JOURNAL ARTICLE
Merve Güneş, Kemal Aktaş, Burçin Yalcın, Ayşen Yağmur Burgazlı, Meltem Asilturk, Ayca Erdem Ünşar, Bülent Kaya
Iron oxide nanoparticles (IONPs) have useful properties, such as strong magnetism and compatibility with living organisms which is preferable for medical applications such as drug delivery and imaging. However, increasing use of these materials, especially in medicine, has raised concerns regarding potential risks to human health. In this study, IONPs were coated with silicon dioxide (SiO2 ), citric acid (CA), and polyethylenimine (PEI) to enhance their dispersion and biocompatibility. Both coated and uncoated IONPs were assessed for genotoxic effects on Drosophila melanogaster...
March 14, 2024: Environmental Toxicology and Pharmacology
https://read.qxmd.com/read/38492564/consult-ii-accurate-taxonomic-identification-and-profiling-using-locality-sensitive-hashing
#20
JOURNAL ARTICLE
Ali Osman Berk Şapcı, Eleonora Rachtman, Siavash Mirarab
MOTIVATION: Taxonomic classification of short reads and taxonomic profiling of metagenomic samples are well-studied yet challenging problems. The presence of species belonging to ranks without close representation in a reference dataset is particularly challenging. While k-mer-based methods have performed well in terms of running time and accuracy, they tend to have reduced accuracy for such novel species. Thus, there is a growing need for methods that combine the scalability of k-merswith increased sensitivity...
March 16, 2024: Bioinformatics
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