As for many model organisms, the amount of omics data produced has recently increased exponentially. There are now >80 published complete genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis. In the last decades, has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5350546 | PMC |
http://dx.doi.org/10.1128/mSystems.00186-16 | DOI Listing |
J Am Soc Mass Spectrom
January 2025
MS Proteomics Research Group, HUN-REN Research Centre for Natural Sciences, Magyar Tudósok körútja 2, H-1117 Budapest, Hungary.
In recent years, alternative enzymes with varied specificities have gained importance in MS-based bottom-up proteomics, offering orthogonal information about biological samples and advantages in certain applications. However, most mass spectrometric workflows are optimized for tryptic digests. This raises the questions of whether enzyme specificity impacts mass spectrometry and if current methods for nontryptic digests are suboptimal.
View Article and Find Full Text PDFHeart Rhythm O2
December 2024
Pfizer Inc, New York, New York.
Background: Prediction models for atrial fibrillation (AF) may enable earlier detection and guideline-directed treatment decisions. However, model bias may lead to inaccurate predictions and unintended consequences.
Objective: The purpose of this study was to validate, assess bias, and improve generalizability of "UNAFIED-10," a 2-year, 10-variable predictive model of undiagnosed AF in a national data set (originally developed using the Indiana Network for Patient Care regional data).
Ther Clin Risk Manag
January 2025
Department of Otolaryngology Head & Neck Surgery, Monash Health, Melbourne, Australia.
Chronic rhinosinusitis with nasal polyps (CRSwNP) is often severe, debilitating and difficult to treat. Recent randomised control trials (RCTs) of biologics that target key inflammatory pathways have demonstrated clinical efficacy in treating CRSwNP. Such RCTs must facilitate meta-analysis.
View Article and Find Full Text PDFIndian J Radiol Imaging
January 2025
Department of Imaging Sciences and Interventional Radiology, Sree Chitra Institute of Medical Sciences, Trivandrum, Kerala, India.
Second part of this statistics primer focuses on advanced statistical concepts continuing on the foundation of basic statistics built from the first part of this primer. This advanced primer aims to delve deeper into essential statistical concepts beyond the basics, equipping the reader with the knowledge to effectively analyze complex data sets, explore correlations and causality, employ regression analysis techniques, interpret survival curves, and evaluate diagnostic tests rigorously. It primarily focuses on the statistical tests used to analyze the relationship between groups of variables (the statistical tests to analyze the difference between groups of variables was discussed in the part 1 of this series).
View Article and Find Full Text PDFMayo Clin Proc Digit Health
December 2024
Department Radiology, Stanford University, Stanford, CA.
Artificial intelligence (AI) and machine learning (ML) are driving innovation in biosciences and are already affecting key elements of medical scholarship and clinical care. Many schools of medicine are capitalizing on the promise of these new technologies by establishing academic units to catalyze and grow research and innovation in AI/ML. At Stanford University, we have developed a successful model for an AI/ML research center with support from academic leaders, clinical departments, extramural grants, and industry partners.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!