Comprehensive Indicator Bank for Resilience of Water Supply Systems

Appropriate indicators are required to measure the resilience of water supply systems (WSSs). However, it is challenging to identify appropriate indicators since there is no comprehensive database of indicators to measure its resiliency. This study will establish a comprehensive bank of indicators to assist water corporations and decision-makers in selecting appropriate indicators for their particular system. The suggested indicator bank is comprised of three layers such as dimension, attributes, and the number of indicators resulting from 12 different indicator codes that the study has analysed. In addition, this paper presents instructions on how the indicator bank can be used and integrated with water enterprises, enabling decision-makers to pick the relevant indicators. The proposed indicator bank is an exploratory approach that should be validated in a real work setting since resilience is a challenging concept, and WSSs are complex due to their dependencies to other lifelines such as power networks with too many variables that may affect the actual outcomes.

Releasing the Kraken

Ten years ago, the dramatic rise in the number of microbial genomes led to an inflection point, when the approach of finding short, exact matches in a comprehensive database became just as accurate as older, slower approaches. The new idea led to a method that was hundreds of times times faster than those that came before. Today, exact k-mer matching is a standard technique at the heart of many microbiome analysis tools.

LungCancer3D: A Comprehensive Database for Integrating Lung Cancer Chromatin Architecture with Other Multi-omics

With the breakthrough of chromatin conformation capture technologies in recent years, the importance of three-dimensional (3D) genome structure in gene expression, cell function regulation, disease occurrence, and development has been gradually recognized. To provide a comprehensive visualization of chromatin architecture and other multi-omics data for lung cancer research, we have constructed a comprehensive database, LungCancer3D (http://www.lungcancer3d.net). This web-based tool focuses on displaying human lung cancer-related HiC data along with a variety of other publicly available data, such as RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, DNA methylation, DNA mutation, and copy number variations. Researchers can visualize these diverse multi-omics data directly through the genome browser and discover how the genes expression is regulated at diverse levels. For example, we have demonstrated that the high expression level of C-MYC in lung cancer may be caused by the distant enhancer introduced by the de novo chromatin loops in lung cancer cells to bind the C-MYC promoter. The integrated multi-omics analyses through the LungCancer3D website can reveal the mechanisms underlying lung cancer development and provide potential targets for lung cancer therapy.

SkewDB: A comprehensive database of GC and a 10 other skews for over 28,000 chromosomes and plasmids

ABSTRACTGC skew denotes the relative excess of G nucleotides over C nucleotides on the leading versus the lagging replication strand of eubacteria. While the effect is small, typically around 2.5%, it is robust and pervasive. GC skew and the analogous TA skew are a localized deviation from Chargaff’s second parity rule, which states that G and C, and T and A occur with (mostly) equal frequency even within a strand.Most bacteria also show the analogous TA skew. Different phyla show different kinds of skew and differing relations between TA and GC skew.This article introduces an open access database (https://skewdb.org) of GC and 10 other skews for over 28,000 chromosomes and plasmids. Further details like codon bias, strand bias, strand lengths and taxonomic data are also included. The SkewDB database can be used to generate or verify hypotheses. Since the origins of both the second parity rule, as well as GC skew itself, are not yet satisfactorily explained, such a database may enhance our understanding of microbial DNA.

MeiosisOnline: A Manually Curated Database for Tracking and Predicting Genes Associated With Meiosis

Meiosis, an essential step in gametogenesis, is the key event in sexually reproducing organisms. Thousands of genes have been reported to be involved in meiosis. Therefore, a specialist database is much needed for scientists to know about the function of these genes quickly and to search for genes with potential roles in meiosis. Here, we developed “MeiosisOnline,” a publicly accessible, comprehensive database of known functional genes and potential candidates in meiosis (https://mcg.ustc.edu.cn/bsc/meiosis/index.html). A total of 2,052 meiotic genes were manually curated from literature resource and were classified into different categories. Annotation information was provided for both meiotic genes and predicted candidates, including basic information, function, protein–protein interaction (PPI), and expression data. On the other hand, 165 mouse genes were predicted as potential candidates in meiosis using the “Greed AUC Stepwise” algorithm. Thus, MeiosisOnline provides the most updated and detailed information of experimental verified and predicted genes in meiosis. Furthermore, the searching tools and friendly interface of MeiosisOnline will greatly help researchers in studying meiosis in an easy and efficient way.