Spartan Daily, December 18, 1941

Volume 30, Issue 58https://scholarworks.sjsu.edu/spartandaily/3378/thumbnail.jp

A comprehensive resource for retrieving, visualizing, and integrating functional genomics data

The enormous amount of freely accessible functional genomics data is an invaluable resource for interrogating the biological function of multiple DNA-interacting players and chromatin modifications by large-scale comparative analyses. However, in practice, interrogating large collections of public data requires major efforts for (i) reprocessing available raw reads, (ii) incorporating quality assessments to exclude artefactual and low-quality data, and (iii) processing data by using high-performance computation. Here, we present qcGenomics, a user-friendly online resource for ultrafast retrieval, visualization, and comparative analysis of tens of thousands of genomics datasets to gain new functional insight from global or focused multidimensional data integration.\ua0\ua9 2019 Blum et al

Chip-scale solar thermal electrical power generation

There is an urgent need for alternative compact technologies that can derive and store energy from the sun, especially the large amount of solar heat that is not effectively used for power generation. Here, we report a combination of solution- and neat-film-based molecular solar thermal (MOST) systems, where solar energy can be stored as chemical energy and released as heat, with microfabricated thermoelectric generators to produce electricity when solar radiation is not available. The photophysical properties of two MOST couples are characterized both in liquid with a catalytical cycling setup and in a phase-interconvertible neat film. Their suitable photophysical properties let us combine them individually with a microelectromechanical ultrathin thermoelectric chip to use the stored solar energy for electrical power generation. The generator can produce, as a proof of concept, a power output of up to 0.1 nW (power output per unit volume up to 1.3 W m−3). Our results demonstrate that such a molecular thermal power generation system has a high potential to store and transfer solar power into electricity and is thus potentially independent of geographical restrictions.This work was supported by the K. & A. Wallenberg Foundation, the Swedish Foundation for Strategic Research, the Swedish Research Council Formas, the Swedish Energy Agency, the European Research Council (ERC) under grant agreement CoG, PHOTHERM - 101002131, the Catalan Institute of Advanced Studies (ICREA), and the European Union's Horizon 2020 Framework Programme under grant agreement no. 951801. The MEMS-TEG chip manufacture and experimentation were supported by the National Natural Science Foundation of China (grant 51776126). The authors would like to thank the Center for Advanced Electronic Materials and Devices (AEMD) and Instrumental Analysis Center of Shanghai Jiao Tong University (SJTU) and the startup fund of Shanghai Jiao Tong University. We thank Dr. Sarah Lerch and Prof. Ben Greatrex for reading and commenting on the manuscript. We acknowledge Neuroncollective.com and Daniel Spacek for the graphical abstract.With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000917-S).Peer reviewe

Gene expression variability in mammalian embryonic stem cells using single cell RNA-seq data

AbstractBackgroundGene expression heterogeneity contributes to development as well as disease progression. Due to technological limitations, most studies to date have focused on differences in mean expression across experimental conditions, rather than differences in gene expression variance. The advent of single cell RNA sequencing has now made it feasible to study gene expression heterogeneity and to characterise genes based on their coefficient of variation.MethodsWe collected single cell gene expression profiles for 32 human and 39 mouse embryonic stem cells and studied correlation between diverse characteristics such as network connectivity and coefficient of variation (CV) across single cells. We further systematically characterised properties unique to High CV genes.ResultsHighly expressed genes tended to have a low CV and were enriched for cell cycle genes. In contrast, High CV genes were co-expressed with other High CV genes, were enriched for bivalent (H3K4me3 and H3K27me3) marked promoters and showed enrichment for response to DNA damage and DNA repair.ConclusionsTaken together, this analysis demonstrates the divergent characteristics of genes based on their CV. High CV genes tend to form co-expression clusters and they explain bivalency at least in part

The SIB Swiss Institute of Bioinformatics’ resources : focus on curated databases

The SIB Swiss Institute of Bioinformatics provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

The Eukaryotic Promoter Database: expansion of EPDnew and new promoter analysis tools

We present an update of EPDNew (http://epd. vital-it. ch), a recently introduced new part of the Eukaryotic Promoter Database (EPD) which has been described in more detail in a previous NAR Database Issue. EPD is an old database of experimentally characterized eukaryotic POL II promoters, which are conceptually defined as transcription initiation sites or regions. EPDnew is a collection of automatically compiled, organism-specific promoter lists complementing the old corpus of manually compiled promoter entries of EPD. This new part is exclusively derived from next generation sequencing data from highthroughput promoter mapping experiments. We report on the recent growth of EPDnew, its extension to additional model organisms and its improved integration with other bioinformatics resources developed by our group, in particular the Signal Search Analysis and ChIP-Seq web servers

The ubiquitin system and jasmonate signaling

The ubiquitin (Ub) system is involved in most, if not all, biological processes in eukaryotes. The major specificity determinants of this system are the E3 ligases, which bind and ubiquitinate specific sets of proteins and are thereby responsible for target recruitment to the proteasome or other cellular processing machineries. The Ub system contributes to the regulation of the production, perception and signal transduction of plant hormones. Jasmonic acid (JA) and its derivatives, known as jasmonates (JAs), act as signaling compounds regulating plant development and plant responses to various biotic and abiotic stress conditions. We provide here an overview of the current understanding of the Ub system involved in JA signaling

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article