Bioinformatics and Genomics

DiscoSnp-RAD: de novo detection of small variants for RAD-Seq population genomics
Tomas Hrbek –– A rapid, efficient and robust tool for analyzing RADseq and other related data. Has the potential to be widely used by the scientific community.
Host transcriptome-guided drug repurposing for COVID-19 treatment: a meta-analysis based approach
David Tollervey –– In the race to develop effective strategies to counter COVID-19, a promising approach is to re-target drugs, for which regulatory approval has already been obtained in a different context. Here the authors re-analyze transcriptomic data to predict candidate targets and potentially therapeutic compounds.
Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution
Andrew Gray –– This article addresses an important question about the heritability of pulmonary function, namely whether this is constant or varies by level of function. This could provide further insight into gene-environment interactions and potentially inform interventions aimed at reducing declines in pulmonary function.
Integrated analysis of lymphocyte infiltration-associated lncRNA for ovarian cancer via TCGA, GTEx and GEO datasets
Walter de Azevedo Jr. –– In this study, Wu et al identified long non-coding RNA-associated competing endogenous RNA (ceRNA) axes that could delineate more reliable prognostic parameters of high-grade serous ovarian cancer, and to examine the long non-coding RNAs’ possible mechanism of in lymphocyte infiltration. The authors were able to define numerous prognostic biomarkers for the incidence and development of high-grade serous ovarian cancer and constructed a network for ceRNA axes.
Identification of key miRNAs in the progression of hepatocellular carcinoma using an integrated bioinformatics approach
Walter de Azevedo Jr. –– Previously studies indicated the association of aberrant expression of microRNAs (miRNAs) and transcriptional factors (TFs) with the development of hepatocellular carcinoma. In work conducted by Zheng et al., the authors investigated potential transcriptomic markers of hepatocellular carcinoma using the analysis of microarray datasets. They used datasets available in the GEO database. Their analysis indicated that two miRNAs—hsa-mir-106b and hsa-mir-195 are identified as potential classifiers of hepatocellular carcinoma.
A non-linear reverse-engineering method for inferring genetic regulatory networks
Walter de Azevedo Jr. –– In this manuscript conducted by Wu et al., the authors proposed a new method to infer the detailed regulatory mechanisms involved in hematopoiesis. This work focused on the development of a computational approach to investigate the effect of possible protein heterodimers and/or synergistic effects on genetic regulation. In summary, the authors proposed a method that is an effective approach to infer the topological structure and dynamic property of genetic regulations.
ECMPride: prediction of human extracellular matrix proteins based on the ideal dataset using hybrid features with domain evidence
Walter de Azevedo Jr. –– In this work conducted by Liu et al, the authors described the development of a new computational tool to study human extracellular matrix proteins. The authors used experimentally verified extracellular matrix datasets and a machine learning model to develop ECMPride, a flexible and scalable computational tool for predicting extracellular matrix proteins. ECMPride has a number of putative extracellular matrix proteins as well as several biological annotations. This tool might contribute to research focused on the identification of members of this important class of proteins.
RNA sequencing of CD4 T-cells reveals the relationships between lncRNA-mRNA co-expression in elite controller vs. HIV-positive infected patients
Walter de Azevedo Jr. –– In the present study, the authors examined the expression profiles of long non-coding RNAs and mRNAs from CD4+ T cells from two elite controllers, two HIV-positive infected patients, and two healthy controls. They built a co-expression network based on the relationships among differentially expressed transcripts and database annotations. So far, this is the first report to examine gene transcription in elite controllers and to investigate their functional relationships. Their results provide a reference for subsequent functional corroboration at the cellular level or even at a molecular scale.
Predicting the risk of sarcopenia in elderly patients with patellar fracture: development and assessment of a new predictive nomogram
Liang Gao –– The authors successfully developed and assessed a new predictive nomogram for predicting the risk of sarcopenia in elderly patients with patellar fractures.
Identification of hub genes and small-molecule compounds in medulloblastoma by integrated bioinformatic analyses
Jafri Abdullah –– Medulloblastoma has different responses to chemotherapy and radiation therapy.
Bioinformatics and Genomics
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100 visitors to my 'Fast computational mutation-response scanning of proteins' article published in #OpenAccess journal @thePeerJ https://t.co/wdLgFqVIWz

Wang et al. examine genome-wide identification and expression analysis of the EXO70 gene family in #grape Read the full @PeerJLife article https://t.co/T3mmrSkx1l #AgriculturalScience #Genomics #MolecularBiology #PlantScience https://t.co/hYpA1iY226

Improving the gnomonic approach with the gnomonicM R-package to estimate natural mortality throughout different life stages https://t.co/1FuhPnrfVq @thePeerJ https://t.co/2SiHVg0uYd

Lu et al. @EinsteinMed present a retrospective study: Neural network analysis of clinical variables predicts escalated care in COVID-19 patients Read the full @PeerJLife article https://t.co/OMLXBQMQyc #MachineLearning #Coronavirus #Pneumonia #InfectiousDiseases https://t.co/y2ni2WCt9I

Historical effective population size of North American hoary bat (Lasiurus cinereus) and challenges to estimating trends in contemporary effective breeding population size from archived samples https://t.co/OkeoMWN0he @thePeerJ https://t.co/Y7wu08Di2L