An open access, peer reviewed electronic journal that covers computational biology, particularly computational methods used in the analysis and annotation of structures.

Bioinformatics and Biology Insights is an open access, peer-reviewed electronic journal that focuses on computational biology, particularly the computational methods used for the analysis and annotation of biological structures.

《Bioinformatics and Biology Insights》是一本开放获取、经过同行评审的电子期刊，专注于计算生物学，尤其是用于结构分析和注释的计算方法。

Bioinformatics and Biology Insights

The human intestinal microbiome is a microbial ecosystem that expresses as many as 100 times more genes than the human host, thereby constituting an important component of the human holobiome, which contributes to multiple health and disease processes. As most commensal species are difficult or impossible to culture, genomic characterization of microbiome composition and function, under various environmental conditions, comprises a central tool in understanding its roles in health and disease. The first decade of microbiome research was mainly characterized by usage of DNA sequencing-based 16S rDNA and shotgun metagenome sequencing, allowing for the elucidation of microbial composition and genome structure. Technological advances in RNA-seq have recently provided us with an ability to gain insight into the genes that are actively expressed in complex bacterial communities, enabling the elucidation of the functional changes that dictate the microbiome functions at given contexts, its interactions with the host, and functional alterations that accompany the conversion of a healthy microbiome toward a disease-driving configuration. Here, we highlight some of the key metatranscriptomics strategies that are implemented to determine microbiota gene expression and its regulation and discuss the advantages and potential challenges associated with these approaches.

Stavros Bashiardes

Gili Zilberman-Schapira

Eran Elinav

Bioinform Biol Insights

Use of Metatranscriptomics in Microbiome Research

Next-generation sequencing technologies have revolutionarily advanced sequence-based research with the advantages of high-throughput, high-sensitivity, and high-speed. RNA-seq is now being used widely for uncovering multiple facets of transcriptome to facilitate the biological applications. However, the large-scale data analyses associated with RNA-seq harbors challenges. In this study, we present a detailed overview of the applications of this technology and the challenges that need to be addressed, including data preprocessing, differential gene expression analysis, alternative splicing analysis, variants detection and allele-specific expression, pathway analysis, co-expression network analysis, and applications combining various experimental procedures beyond the achievements that have been made. Specifically, we discuss essential principles of computational methods that are required to meet the key challenges of the RNA-seq data analyses, development of various bioinformatics tools, challenges associated with the RNA-seq applications, and examples that represent the advances made so far in the characterization of the transcriptome.

Yixing Han

Shouguo Gao

Kathrin Muegge

Wei Zhang

Bing Zhou

Advanced Applications of RNA Sequencing and Challenges

Human papillomavirus (HPV) causes disease through complex interactions between viral and host proteins, with the PI3K signaling pathway playing a key role. Proteins like AKT, IQGAP1, and MMP16 are involved in HPV-related cancer development. Traditional methods for studying protein-protein interactions (PPIs) are labor-intensive and time-consuming. Computational models are becoming more popular as they are less labor-intensive and often more efficient. This study aimed to develop a deep learning model to predict interactions between HPV and host proteins.

Sheila Santa

Samuel Kojo Kwofie

Kwasi Agyenkwa-Mawuli

Osbourne Quaye

Charles A Brown

Emmanuel A Tagoe

Prediction of Human Papillomavirus-Host Oncoprotein Interactions Using Deep Learning

使用深度学习预测人乳头瘤病毒与宿主癌蛋白相互作用

Environmental pollution has become a worldwide concern that requires rigorous efforts from all sectors of society to monitor, control, and remediate it. In environmental pollution control,

Duguma Dibbisa

Tadesse Daba

Seid Mohammed

Regulatory Element Analysis and Comparative Genomics Study of Heavy Metal-Resistant Genes in the Complete Genome <i>of Cupriavidus gilardii</i> CR3

铜绿假单胞菌CR3全基因组中重金属抗性基因的调控元件分析与比较基因组学研究

Background: Coronary artery disease (CAD) is one of the leading causes of death worldwide. The buildup of atherosclerotic plaque, including lipids and cellular waste, characterizes this disease. Smooth muscle cells (SMCs) can migrate and proliferate to form a fibrous cap that stabilizes the atherosclerotic plaque in response to plaque buildup. However, in some severe cases, the fibrous cap is unable to prevent plaque rupture, which can lead to a thrombotic event causing a stroke or myocardial infarction. Studies have been conducted to identify genes associated with this disease. However, the influence of sex on CAD risk is poorly understood due to the complexity of the disease and the lack of women in clinical studies. Methods: This study is investigated with a unique collection of human aortic smooth muscle cells (huASMCs) derived from 118 male and 33 female individuals who either underwent a heart transplant or were victims of motor vehicle accidents. In this investigation, we explore differentially expressed genes between males and females related to atherosclerosis using a unique RNAseq dataset of human aortic SMCs. Results: Our study identified 8 genes ( CHST1, DKK2, DLL4, EIF1AXP1, GALNT13, NOTCH4, SELL, SPARCL1) that exhibit sex-biased effects in SMCs. Of these, 6 genes were found in the Athero-Express dataset and 5 of them were associated with atherosclerosis-relevant phenotypes. We discovered a novel NOTCH4/DLL4 pathway that plays a role in the differential expression of these genes between males and females. This pathway is linked to coronary artery physiology and may play a role in the pathophysiology of coronary artery disease that differs between the sexes. Conclusions: Overall, this investigation shows that differentially expressed genes between males and females in human aortic SMCs exist.

Sarah L Meng

Rita Anane-Wae

Ernest Diez Benavente

Redouane Aherrahrou

System Genetics Analysis Reveals Sex Differences in Human Aortic Smooth Muscle Gene Expression

系统遗传学分析揭示人类主动脉平滑肌基因表达的性别差异

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a high transmissibility profile which favors the accumulation of mutations along its genome, providing the emergence of new variants. In this context, haplotype studies have allowed mapping specific regions and combining approaches and tracking phylogenetic changes. During the COVID-19 pandemic, it was notorious that home environments favored the circulation of SARS-CoV-2, in this study we evaluated 1,407 individuals positive for SARS-CoV-2, in which we located 53 families in the period from June 2021 to February 2023. The epidemiological data were collected in E-SUS notifica and SIVEP-gripe. Then, the genetic material was extracted using the commercial kit and the viral load was evaluated and the viral genomes were sequenced using the Illumina MiSeq methodology. In addition, the circulation of 3 variants and their respective subvariants was detected. The delta variant represented the highest number of cases with 45%, the Omicron variant 43% and the lowest number with 11% of cases the Gamma variants. There were cases of families infected by different subvariants, thus showing different sources of infection. The haplotype network showed a distribution divided into 6 large clusters that were established according to the genetic characteristics observed by the algorithm and 224 Parsimony informative sites were found. In addition, 92% of subjects were symptomatic and 8% asymptomatic. The secondary attack rate of this study was 8.32%. Therefore, we can infer that the home environment favors the spread of SARS-CoV-2, so it is of paramount importance to carry out genomic surveillance in specific groups such as intradomiciliary ones.

Karolaine Santos Teixeira

Márlon Grégori Flores Custódio

Gabriella Sgorlon

Tárcio Peixoto Roca

Jackson Alves da Silva Queiroz

Ana Maisa Passos-Silva

Jessiane Ribeiro

Deusilene Vieira

Haplotypic Distribution of SARS-CoV-2 Variants in Cases of Intradomiciliary Infection in the State of Rondônia, Western Amazon

SARS-CoV-2变异株单倍型在家内感染病例中的分布：亚马逊西部罗赖马州的研究

The initial step in pre-mRNA splicing involves formation of a spliceosome commitment complex (CC) or E-complex by factors that serve to bind and mark the exon-intron boundaries that will undergo splicing. The CC component U1 snRNP assembles at the 5'-splice site (ss), whereas SF1, U2AF2, and U2AF1 define the 3'-ss of the intron. A PRP40 protein bridges U1 snRNP with factors at the 3'-ss. To determine how defects in CC components impact cancers, we analyzed human gastrointestinal (GI) cancer patient tissue and clinical data from cBioPortal. cBioPortal datasets were analyzed for CC factor alterations and patient outcomes in GI cancers (bowel, stomach, esophagus, pancreas, and liver). In addition, co-expression datasets were used to determine the splicing targets of the CC. Our analysis found that frequency of genetic changes was low (1%-13%), but when combined with changes in expression levels, there was an overall surprisingly high incidence of CC component (>30%) alterations in GI cancers. Colon cancer patients carrying

Yun Zhang

Alexandria Carrasquillo Simko

Uzondu Okoro

Deja Jamese Sibert

Jin Hyung Moon

Bin Liu

Angabin Matin

Commitment Complex Splicing Factors in Cancers of the Gastrointestinal Tract—An In Silico Study

胃肠道癌中的复杂剪接因子——一项计算机模拟研究

短名	Bioinform Biol Insights
Journal Impact	2.33
国际分区	BIOCHEMICAL RESEARCH METHODS(Q3)

ISSN	1177-9322
h-index	32

涉及主题	生物化学遗传学生物化学基因计算生物学医学计算机科学生物信息学物理内科学数学基因表达人工智能基因组
出版信息	出版商: Libertas Academica Ltd.，出版周期: ，期刊类型: journal，开源期刊: 是
基本数据	创刊年份: 2009，原创研究文献占比: 97.73%，自引率:0.00%， Gold OA占比: 95.65%
期刊费用	$2650详情
平均审稿周期	网友分享经验：8 Weeks

Bioinformatics and Biology Insights

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Use of Metatranscriptomics in Microbiome Research

Advanced Applications of RNA Sequencing and Challenges

Prediction of Human Papillomavirus-Host Oncoprotein Interactions Using Deep Learning

Regulatory Element Analysis and Comparative Genomics Study of Heavy Metal-Resistant Genes in the Complete Genome of Cupriavidus gilardii CR3

System Genetics Analysis Reveals Sex Differences in Human Aortic Smooth Muscle Gene Expression

Prediction of Human Papillomavirus-Host Oncoprotein Interactions Using Deep Learning

Regulatory Element Analysis and Comparative Genomics Study of Heavy Metal-Resistant Genes in the Complete Genome of Cupriavidus gilardii CR3

System Genetics Analysis Reveals Sex Differences in Human Aortic Smooth Muscle Gene Expression

Haplotypic Distribution of SARS-CoV-2 Variants in Cases of Intradomiciliary Infection in the State of Rondônia, Western Amazon

Commitment Complex Splicing Factors in Cancers of the Gastrointestinal Tract—An In Silico Study