Journal of bioinformatics and systems biology : Open access最新文献_第2页

The Growing Liberality Observed in Primary Animal and Plant Cultures is Common to the Social Amoeba. 在原始动物和植物培养中观察到的日益增长的慷慨是社会变形虫的共同特点。

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 DOI: 10.26502/jbsb.5107045

Norichika Ogata

引用次数: 1

Control of Expression Level in Human Genes: Observations with Apoptosis Genes and Genes Involved in B cell Development 人类基因表达水平的控制:凋亡基因和参与B细胞发育的基因的观察

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 DOI: 10.26502/jbsb.5107038

Jay C. Brown

引用次数: 0

Criteria for the Evaluation of Workflow Management Systems for Scientific Data Analysis 科学数据分析工作流程管理系统评价标准

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 DOI: 10.26502/jbsb.5107055

Aleyna Dilan Kiran, Mehmet Can Ay, J. Allmer

{"title":"Criteria for the Evaluation of Workflow Management Systems for Scientific Data Analysis","authors":"Aleyna Dilan Kiran, Mehmet Can Ay, J. Allmer","doi":"10.26502/jbsb.5107055","DOIUrl":"https://doi.org/10.26502/jbsb.5107055","url":null,"abstract":"Many scientific endeavors, such as molecular biology, have become dependent on big data and its analysis. For example, precision medicine depends on molecular measurements and data analysis per patient. Data analyses supporting medical decisions must be standardized and performed consistently across patients. While perhaps not life-threatening, data analyses in basic research have become increasingly complex. RNA-seq data, for example, entails a multi-step analysis ranging from quality assessment of the measurements to statistical analyses. Workflow management systems (WFMS) enable the development of data analysis workflows (WF), their reproduction, and their application to datasets of the same type. However, far more than a hundred WFMS are available, and there is no way to convert data analysis WFs among WFMS. Therefore, the initial choice of a WFMS is important as it entails a lock-in to the system. The reach in their particular field (number of citations) can be used as a proxy for selecting a WFMS, but of the about 25 WFMS we mention in this work, at least 5 have a large reach in scientific data analysis. Hence other criteria are needed to delineate among WFMS. By extracting such criteria from selected studies concerning WFMS and adding additional criteria, we arrived at five critical criteria: reproducibility, reusability, FAIRness, versioning support, and security. Another five criteria (providing a graphical user interface, WF flexibility, WF scalability, WF shareability, and computational transparency) we deemed important but not critical for the assessment of WFMS. We applied the criteria to the most cited WFMS in PubMed and found none that support all criteria. We hope that suggesting these criteria will spark a discussion on what features are important for WFMS in scientific data analysis and may lead to developing WFMS that fulfill such criteria.","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69367943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RLSuite: An Integrative R-Loop Bioinformatics Framework. RLSuite：RLSuite: An Integrative R-Loop Bioinformatics Framework.

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 Epub Date: 2023-12-21 DOI: 10.26502/jbsb.5107071

H E Miller, D Montemayor, S Levy, K Sharma, B Frost, A J R Bishop

{"title":"RLSuite: An Integrative R-Loop Bioinformatics Framework.","authors":"H E Miller, D Montemayor, S Levy, K Sharma, B Frost, A J R Bishop","doi":"10.26502/jbsb.5107071","DOIUrl":"10.26502/jbsb.5107071","url":null,"abstract":"We recently described the development of a database of 810 R-loop mapping datasets and used this data to conduct a meta-analysis of R-loops. R-loops are three-stranded nucleic acid structures containing RNA:DNA hybrids and we were able to verify that 30% of expressed genes have an associated R-loop in a location conserved manner.. Moreover, intergenic R-loops map to enhancers, super enhancers and with TAD domain boundaries. This work demonstrated that R-loop mapping via high-throughput sequencing can reveal novel insight into R-loop biology, however the analysis and quality control of these data is a non-trivial task for which few bioinformatic tools exist. Herein we describe RLSuite, an integrative R-loop bioinformatics framework for pre-processing, quality control, and downstream analysis of R-loop mapping data. RLSuite enables users to compare their data to hundreds of public datasets and generate a user-friendly analysis report for sharing with non-bioinformatician colleagues. Taken together, RLSuite is a novel analysis framework that should greatly benefit the emerging R-loop bioinformatics community in a rapidly expanding aspect of epigenetic control that is still poorly understood.","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"6 4","pages":"364-378"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10827345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139643520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novornabreak: Local Assembly for Novel Splice Junction and Fusion Transcript Detection from RNA-Seq Data. Novornabreak：从 RNA-Seq 数据中检测新型剪接接头和融合转录本的局部组装。

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 Epub Date: 2023-04-04 DOI: 10.26502/jbsb.5107050

Yukun Tan, Vakul Mohanty, Shaoheng Liang, Jinzhuang Dou, Jun Ma, Kun Hee Kim, Marc Jan Bonder, Xinghua Shi, Charles Lee, Zechen Chong, Ken Chen

{"title":"Novornabreak: Local Assembly for Novel Splice Junction and Fusion Transcript Detection from RNA-Seq Data.","authors":"Yukun Tan, Vakul Mohanty, Shaoheng Liang, Jinzhuang Dou, Jun Ma, Kun Hee Kim, Marc Jan Bonder, Xinghua Shi, Charles Lee, Zechen Chong, Ken Chen","doi":"10.26502/jbsb.5107050","DOIUrl":"https://doi.org/10.26502/jbsb.5107050","url":null,"abstract":"We present novoRNABreak, a unified framework for cancer specific novel splice junction and fusion transcript detection in RNA-seq data obtained from human cancer samples. novoRNABreak is based on a local assembly model, which offers a tradeoff between the alignment-based and de novo whole transcriptome assembly (WTA) methods. This approach is accurate and sensitive in assembling novel junctions that are difficult to directly align or have multiple alignments. Additionally, it is more efficient due to the strategy that focuses on junctions rather than full length transcripts. The performance of novoRNABreak is demonstrated by a comprehensive set of experiments using synthetic data generated based on genome reference, as well as real RNA-seq data from breast cancer and prostate cancer samples. The results show that our tool has a better performance by fully utilizing unmapped reads and precisely identifying the junctions where short reads or small exons have multiple alignments. novoRNABreak is a fully-fledged program available on GitHub (https://github.com/KChen-lab/novoRNABreak).","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"6 2","pages":"74-81"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11412692/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Constrained disorder principle-based second-generation algorithms implement quantified variability signatures to improve the function of complex systems 基于约束无序原理的第二代算法实现了量化的可变性特征，以改善复杂系统的功能

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 DOI: 10.26502/jbsb.5107051

Tal Sigawi, Hillel Lehmann, N. Hurvitz, Y. Ilan

引用次数: 4

Bioinformatic Analysis of Transcriptional Regulation by Nur77 in Central Nervous System and Immune System 中枢神经系统和免疫系统中Nur77转录调控的生物信息学分析

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 DOI: 10.26502/jbsb.5107056

Faunes F, Andrés Me, Olivares-Costa M

引用次数: 0

CDKs Functional Analysis in Low Proliferating Early-Stage Pancreatic Ductal Adenocarcinoma. CDKs在低增殖早期胰腺导管腺癌中的功能分析。

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 Epub Date: 2023-08-16 DOI: 10.26502/jbsb.5107060

Shikai Zhu, Huining Yang, Lingling Liu, Zhilin Jiang, Juanjuan Ji, Xiao Wang, Lin Zhong, Fulin Liu, Xueliang Gao, Haizhen Wang, Yu Zhou

{"title":"CDKs Functional Analysis in Low Proliferating Early-Stage Pancreatic Ductal Adenocarcinoma.","authors":"Shikai Zhu, Huining Yang, Lingling Liu, Zhilin Jiang, Juanjuan Ji, Xiao Wang, Lin Zhong, Fulin Liu, Xueliang Gao, Haizhen Wang, Yu Zhou","doi":"10.26502/jbsb.5107060","DOIUrl":"10.26502/jbsb.5107060","url":null,"abstract":"Pancreatic ductal adenocarcinoma (PDAC) is a highly devastating disease with a poor prognosis and growing incidence. In this study, we explored the potential roles of CDK1, CDK2, CDK4, and CDK6 in the progression of early-stage PDAC. Clinicopathologic and mRNA expression data and treatment information of 140 patients identified with stage I/II PDAC who underwent pancreaticoduodenectomy were obtained from the Cancer Genome Atlas data set. Our bioinformatic analysis showed that higher CDK1, CDK2, CDK4, or CDK6 expression was associated with a shorter median survival of the early-stage PDAC patients. Of note, in the low-proliferating pancreatic cancer group, CDKs expressions were significantly associated with proteins functioning in apoptosis, metastasis, immunity, or stemness. Among the low-proliferating PDAC, higher expression of CDK1 was associated with the shorter survival of patients, suggesting that CDK1 may regulate PDAC progression through cell cycle-independent mechanisms. Our experimental data showed that CDK1 knockdown/inhibition significantly suppressed the expression levels of AHR and POU5F1, two critical proteins functioning in cancer cell metastasis and stemness, in low-proliferating, but not in high-proliferating pancreatic cancer cells. In all, our study suggests that CDKs regulate PDAC progression not only through cell proliferation but also through apoptosis, metastasis, immunity, and stemness.","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"6 3","pages":"187-200"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516534/pdf/nihms-1926474.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41156658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SMS: A Novel Approach for Bacterial Strain Analysis in Multiple Samples SMS:多样本细菌菌株分析的新方法

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 DOI: 10.26502/jbsb.5107065

Saidi Wang, Minerva Fatimae Ventolero, Haiyan Hu, Xiaoman Li

引用次数: 0

A Computational Pipeline to Control the Quality and Reduce Contamination in Single Retinal Ganglion Cells 控制单个视网膜神经节细胞质量和减少污染的计算管道

Journal of bioinformatics and systems biology : Open access Pub Date : 2023-01-01 DOI: 10.26502/jbsb.5107061

Yeganeh Madadi, Hao Chen, Lu Lu, Monica M Jablonski, Robert W Williams, Siamak Yousefi

{"title":"A Computational Pipeline to Control the Quality and Reduce Contamination in Single Retinal Ganglion Cells","authors":"Yeganeh Madadi, Hao Chen, Lu Lu, Monica M Jablonski, Robert W Williams, Siamak Yousefi","doi":"10.26502/jbsb.5107061","DOIUrl":"https://doi.org/10.26502/jbsb.5107061","url":null,"abstract":"Single-cell transcriptome profiling has transformed our understanding of cellular heterogeneity. However, single-cell data with poor quality can impede proper identification of distinct cell populations and subsequent biological interpretations. In this study, we present a customized computational approach to control the quality and reduce contaminations in single-cell transcriptome profiling of retinal ganglion cells (RGCs). We leverage domain knowledge and statistical methods to effectively eliminate various sources of contaminants for identification of RGC types and subtypes. We show that our end-to-end computational pipeline improves the accuracy and reliability of single-cell transcriptome profiling of RGCs and enhances the biological interpretations. To show the effectiveness of our pipeline, we use 5,994 RGCs captured from retinas of mouse using Fluidigm technology as a benchmark dataset and compare with widely used quality control tools. Further, we introduce seven candidate F-RGC subtype markers that we identified after applying our introduced pipeline on the benchmark dataset. Our customized quality control pipeline could enable retinal single RGC probing with more granularity, leading to new insights into RGC-related visual diseases and development of therapeutic approaches.","PeriodicalId":73617,"journal":{"name":"Journal of bioinformatics and systems biology : Open access","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69367526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0