journal
https://read.qxmd.com/read/38802748/ling3d-visualizing-the-spatio-temporal-dynamics-of-clonal-evolution
#1
JOURNAL ARTICLE
Anjun Hu, Awino Maureiq E Ojwang', Kayode D Olumoyin, Katarzyna A Rejniak
BACKGROUND: Cancers are spatially heterogenous, thus their clonal evolution, especially following anti-cancer treatments, depends on where the mutated cells are located within the tumor tissue. For example, cells exposed to different concentrations of drugs, such as cells located near the vessels in contrast to those residing far from the vasculature, can undergo a different evolutionary path. However, classical representations of cell lineage trees do not account for this spatial component of emerging cancer clones...
May 27, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38802733/seda-2024-update-enhancing-the-sequence-dataset-builder-for-seamless-integration-into-automated-data-analysis-pipelines
#2
JOURNAL ARTICLE
Miguel Reboiro-Jato, Daniel Pérez-Rodríguez, Miguel José Da Silva, David Vila-Fernández, Cristina P Vieira, Jorge Vieira, Hugo López-Fernández
BACKGROUND: The initial version of SEDA assists life science researchers without programming skills with the preparation of DNA and protein sequence FASTA files for multiple bioinformatics applications. However, the initial version of SEDA lacks a command-line interface for more advanced users and does not allow the creation of automated analysis pipelines. RESULTS: The present paper discusses the updates of the new SEDA release, including the addition of a complete command-line interface, new functionalities like gene annotation, a framework for automated pipelines, and improved integration in Linux environments...
May 27, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38789933/maboss-for-hpc-environments-implementations-of-the-continuous-time-boolean-model-simulator-for-large-cpu-clusters-and-gpu-accelerators
#3
JOURNAL ARTICLE
Adam Šmelko, Miroslav Kratochvíl, Emmanuel Barillot, Vincent Noël
BACKGROUND: Computational models in systems biology are becoming more important with the advancement of experimental techniques to query the mechanistic details responsible for leading to phenotypes of interest. In particular, Boolean models are well fit to describe the complexity of signaling networks while being simple enough to scale to a very large number of components. With the advance of Boolean model inference techniques, the field is transforming from an artisanal way of building models of moderate size to a more automatized one, leading to very large models...
May 24, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38789920/improving-replicability-in-single-cell-rna-seq-cell-type-discovery-with-dune
#4
JOURNAL ARTICLE
Hector Roux de Bézieux, Kelly Street, Stephan Fischer, Koen Van den Berge, Rebecca Chance, Davide Risso, Jesse Gillis, John Ngai, Elizabeth Purdom, Sandrine Dudoit
BACKGROUND: Single-cell transcriptome sequencing (scRNA-Seq) has allowed new types of investigations at unprecedented levels of resolution. Among the primary goals of scRNA-Seq is the classification of cells into distinct types. Many approaches build on existing clustering literature to develop tools specific to single-cell. However, almost all of these methods rely on heuristics or user-supplied parameters to control the number of clusters. This affects both the resolution of the clusters within the original dataset as well as their replicability across datasets...
May 24, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38769505/prcrs-a-prediction-model-of-severe-crs-in-car-t-therapy-based-on-transfer-learning
#5
JOURNAL ARTICLE
Zhenyu Wei, Chengkui Zhao, Min Zhang, Jiayu Xu, Nan Xu, Shiwei Wu, Xiaohui Xin, Lei Yu, Weixing Feng
BACKGROUND: CAR-T cell therapy represents a novel approach for the treatment of hematologic malignancies and solid tumors. However, its implementation is accompanied by the emergence of potentially life-threatening adverse events known as cytokine release syndrome (CRS). Given the escalating number of patients undergoing CAR-T therapy, there is an urgent need to develop predictive models for severe CRS occurrence to prevent it in advance. Currently, all existing models are based on decision trees whose accuracy is far from meeting our expectations, and there is a lack of deep learning models to predict the occurrence of severe CRS more accurately...
May 20, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38769492/hmmf-a-hybrid-multi-modal-fusion-framework-for-predicting-drug-side-effect-frequencies
#6
JOURNAL ARTICLE
Wuyong Liu, Jingyu Zhang, Guanyu Qiao, Jilong Bian, Benzhi Dong, Yang Li
BACKGROUND: The identification of drug side effects plays a critical role in drug repositioning and drug screening. While clinical experiments yield accurate and reliable information about drug-related side effects, they are costly and time-consuming. Computational models have emerged as a promising alternative to predict the frequency of drug-side effects. However, earlier research has primarily centered on extracting and utilizing representations of drugs, like molecular structure or interaction graphs, often neglecting the inherent biomedical semantics of drugs and side effects...
May 20, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38760692/semi-quantitative-group-testing-for-efficient-and-accurate-qpcr-screening-of-pathogens-with-a-wide-range-of-loads
#7
JOURNAL ARTICLE
Ananthan Nambiar, Chao Pan, Vishal Rana, Mahdi Cheraghchi, João Ribeiro, Sergei Maslov, Olgica Milenkovic
BACKGROUND: Pathogenic infections pose a significant threat to global health, affecting millions of people every year and presenting substantial challenges to healthcare systems worldwide. Efficient and timely testing plays a critical role in disease control and transmission prevention. Group testing is a well-established method for reducing the number of tests needed to screen large populations when the disease prevalence is low. However, it does not fully utilize the quantitative information provided by qPCR methods, nor is it able to accommodate a wide range of pathogen loads...
May 17, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38755561/characterization-of-telomere-variant-repeats-using-long-reads-enables-allele-specific-telomere-length-estimation
#8
JOURNAL ARTICLE
Zachary Stephens, Jean-Pierre Kocher
Telomeres are regions of repetitive DNA at the ends of linear chromosomes which protect chromosome ends from degradation. Telomere lengths have been extensively studied in the context of aging and disease, though most studies use average telomere lengths which are of limited utility. We present a method for identifying all 92 telomere alleles from long read sequencing data. Individual telomeres are identified using variant repeats proximal to telomere regions, which are unique across alleles. This high-throughput and high-resolution characterization of telomeres could be foundational to future studies investigating the roles of specific telomeres in aging and disease...
May 17, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38755527/amrviz-enables-seamless-genomics-analysis-and-visualization-of-antimicrobial-resistance
#9
JOURNAL ARTICLE
Duc Quang Le, Son Hoang Nguyen, Tam Thi Nguyen, Canh Hao Nguyen, Tho Huu Ho, Nam S Vo, Trang Nguyen, Hoang Anh Nguyen, Minh Duc Cao
We have developed AMRViz, a toolkit for analyzing, visualizing, and managing bacterial genomics samples. The toolkit is bundled with the current best practice analysis pipeline allowing researchers to perform comprehensive analysis of a collection of samples directly from raw sequencing data with a single command line. The analysis results in a report showing the genome structure, genome annotations, antibiotic resistance and virulence profile for each sample. The pan-genome of all samples of the collection is analyzed to identify core- and accessory-genes...
May 16, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38750431/mr-ggi-accurate-inference-of-gene-gene-interactions-using-mendelian-randomization
#10
JOURNAL ARTICLE
Wonseok Oh, Junghyun Jung, Jong Wha J Joo
BACKGROUND: Researchers have long studied the regulatory processes of genes to uncover their functions. Gene regulatory network analysis is one of the popular approaches for understanding these processes, requiring accurate identification of interactions among the genes to establish the gene regulatory network. Advances in genome-wide association studies and expression quantitative trait loci studies have led to a wealth of genomic data, facilitating more accurate inference of gene-gene interactions...
May 15, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38750423/readsynth-short-read-simulation-for-consideration-of-composition-biases-in-reduced-metagenome-sequencing-approaches
#11
JOURNAL ARTICLE
Ryan Kuster, Margaret Staton
BACKGROUND: The application of reduced metagenomic sequencing approaches holds promise as a middle ground between targeted amplicon sequencing and whole metagenome sequencing approaches but has not been widely adopted as a technique. A major barrier to adoption is the lack of read simulation software built to handle characteristic features of these novel approaches. Reduced metagenomic sequencing (RMS) produces unique patterns of fragmentation per genome that are sensitive to restriction enzyme choice, and the non-uniform size selection of these fragments may introduce novel challenges to taxonomic assignment as well as relative abundance estimates...
May 15, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38745336/correction-nanoberta-asp-predicting-nanobody-paratope-based-on-a-pretrained-roberta-model
#12
Shangru Li, Xiangpeng Meng, Rui Li, Bingding Huang, Xin Wang
No abstract text is available yet for this article.
May 14, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38745271/primerevalpy-a-tool-for-in-silico-evaluation-of-primers-for-targeting-the-microbiome
#13
JOURNAL ARTICLE
Lara Vázquez-González, Alba Regueira-Iglesias, Carlos Balsa-Castro, Nicolás Vila-Blanco, Inmaculada Tomás, María J Carreira
BACKGROUND: The selection of primer pairs in sequencing-based research can greatly influence the results, highlighting the need for a tool capable of analysing their performance in-silico prior to the sequencing process. We therefore propose PrimerEvalPy, a Python-based package designed to test the performance of any primer or primer pair against any sequencing database. The package calculates a coverage metric and returns the amplicon sequences found, along with information such as their average start and end positions...
May 14, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38745112/multi-class-boosting-for-the-analysis-of-multiple-incomplete-views-on-microbiome-data
#14
JOURNAL ARTICLE
Andrea Simeon, Miloš Radovanović, Tatjana Lončar-Turukalo, Michelangelo Ceci, Sanja Brdar, Gianvito Pio
BACKGROUND: Microbiome dysbiosis has recently been associated with different diseases and disorders. In this context, machine learning (ML) approaches can be useful either to identify new patterns or learn predictive models. However, data to be fed to ML methods can be subject to different sampling, sequencing and preprocessing techniques. Each different choice in the pipeline can lead to a different view (i.e., feature set) of the same individuals, that classical (single-view) ML approaches may fail to simultaneously consider...
May 14, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38741200/neighborhood-based-computational-approaches-for-the-prediction-of-lncrna-disease-associations
#15
JOURNAL ARTICLE
Mariella Bonomo, Simona E Rombo
MOTIVATION: Long non-coding RNAs (lncRNAs) are a class of molecules involved in important biological processes. Extensive efforts have been provided to get deeper understanding of disease mechanisms at the lncRNA level, guiding towards the detection of biomarkers for disease diagnosis, treatment, prognosis and prevention. Unfortunately, due to costs and time complexity, the number of possible disease-related lncRNAs verified by traditional biological experiments is very limited. Computational approaches for the prediction of disease-lncRNA associations allow to identify the most promising candidates to be verified in laboratory, reducing costs and time consuming...
May 13, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38730374/carex-context-aware-read-extension-of-paired-end-sequencing-data
#16
JOURNAL ARTICLE
Felix Kallenborn, Bertil Schmidt
BACKGROUND: Commonly used next generation sequencing machines typically produce large amounts of short reads of a few hundred base-pairs in length. However, many downstream applications would generally benefit from longer reads. RESULTS: We present CAREx-an algorithm for the generation of pseudo-long reads from paired-end short-read Illumina data based on the concept of repeatedly computing multiple-sequence-alignments to extend a read until its partner is found...
May 10, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38730317/machine-learning-based-dna-melt-curve-profiling-enables-automated-novel-genotype-detection
#17
JOURNAL ARTICLE
Aaron Boussina, Lennart Langouche, Augustine C Obirieze, Mridu Sinha, Hannah Mack, William Leineweber, April Aralar, David T Pride, Todd P Coleman, Stephanie I Fraley
Surveillance for genetic variation of microbial pathogens, both within and among species, plays an important role in informing research, diagnostic, prevention, and treatment activities for disease control. However, large-scale systematic screening for novel genotypes remains challenging in part due to technological limitations. Towards addressing this challenge, we present an advancement in universal microbial high resolution melting (HRM) analysis that is capable of accomplishing both known genotype identification and novel genotype detection...
May 10, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38724920/prediction-of-anticancer-drug-sensitivity-using-an-interpretable-model-guided-by-deep-learning
#18
JOURNAL ARTICLE
Weixiong Pang, Ming Chen, Yufang Qin
BACKGROUND: The prediction of drug sensitivity plays a crucial role in improving the therapeutic effect of drugs. However, testing the effectiveness of drugs is challenging due to the complex mechanism of drug reactions and the lack of interpretability in most machine learning and deep learning methods. Therefore, it is imperative to establish an interpretable model that receives various cell line and drug feature data to learn drug response mechanisms and achieve stable predictions between available datasets...
May 9, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38724908/biclustering-analysis-on-tree-shaped-time-series-single-cell-gene-expression-data-of-caenorhabditis-elegans
#19
JOURNAL ARTICLE
Qi Guan, Xianzhong Yan, Yida Wu, Da Zhou, Jie Hu
BACKGROUND: In recent years, gene clustering analysis has become a widely used tool for studying gene functions, efficiently categorizing genes with similar expression patterns to aid in identifying gene functions. Caenorhabditis elegans is commonly used in embryonic research due to its consistent cell lineage from fertilized egg to adulthood. Biologists use 4D confocal imaging to observe gene expression dynamics at the single-cell level. However, on one hand, the observed tree-shaped time-series datasets have characteristics such as non-pairwise data points between different individuals...
May 9, 2024: BMC Bioinformatics
https://read.qxmd.com/read/38724907/omd-curation-toolkit-a-workflow-for-in-house-curation-of-public-omics-datasets
#20
JOURNAL ARTICLE
Samuel Piquer-Esteban, Vicente Arnau, Wladimiro Diaz, Andrés Moya
BACKGROUND: Major advances in sequencing technologies and the sharing of data and metadata in science have resulted in a wealth of publicly available datasets. However, working with and especially curating public omics datasets remains challenging despite these efforts. While a growing number of initiatives aim to re-use previous results, these present limitations that often lead to the need for further in-house curation and processing. RESULTS: Here, we present the Omics Dataset Curation Toolkit (OMD Curation Toolkit), a python3 package designed to accompany and guide the researcher during the curation process of metadata and fastq files of public omics datasets...
May 9, 2024: BMC Bioinformatics
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