Bioinformatics and Genomics

Editors' Picks

Adaptive divergence for rapid adversarial optimization
Charles Elkan –– Generative adversarial networks (GANs) are an exciting development in machine learning, but it is hard to make them work in practice, and they can require a lot of training data. This research is a significant step towards making GANs more usable.
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.
The mitochondrial genome of Acrobeloides varius (Cephalobomorpha) confirms non-monophyly of Tylenchina (Nematoda)
Jia-Yong Zhang –– This research provide the complete mitochondrial genome of Acrobeloides varius.
The spindle assembly checkpoint and speciation
Ugo Bastolla –– This paper is important in the context of sympatric speciation, where it supports a speciation mechanism based on the variation of the number of chromosomes through sound molecular biology reasoning and mathematical modelling.
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.
Bioinformatics and Genomics

Section discussions

An improved similarity-based approach to predicting and mapping #Soil #OrganicCarbon and soil #TotalNitrogen in a coastal region of northeastern China

Exact integer linear programming solvers outperform simulated annealing for solving conservation planning problems @thePeerJ

Characterization of the bacterial microbiota composition and #evolution at different intestinal tract in wild pigs (Sus scrofa ussuricus) @thePeerJ

Microbiome analysis by primmorphs. Took more than year to publish с помощью @thePeerJ

22 hours ago
7 immune-related risk signatures of HCC via @thePeerJ

My article has been published today in @thePeerJ #Biodiversity #MolecularBiology #PlantScience