Germline genetic variation contributes to cancer etiology, but self-reported race is not always consistent with genetic ancestry, and samples may not have identifying ancestry information. In this study, we describe a flexible computational pipeline, PopInf, to visualize principal component analysis output and assign ancestry to samples with unknown genetic ancestry, given a reference population panel

Autism spectrum disorder (ASD) is a neurological and developmental disorder. Traditional diagnosis of ASD is typically performed through the observation of behaviors and interview of a patient. However, these diagnosis methods are time-consuming and can be misleading sometimes. Integrating machine learning algorithms with neuroimages, a diagnosis method, can possibly be established to detect ASD subjects

Earlier analysis of the Protein Data Bank derived the distribution of rotations from the plane of a protein hydrogen bond donor peptide group to the plane of its acceptor peptide group. The quasi Boltzmann formalism of Pohl–Finkelstein is employed to estimate free energies of protein elements with these hydrogen bonds, pinpointing residues with a high propensity for conformational change. This is applied

Previous studies revealed that PBX1 ranked the third in the differentially expressed genes about development and progression of breast cancer (BC). Nevertheless, the role of PBX1 contributing to progression of BC has been unevaluated. Here, on the basis of ONCOMINE and GOBO databases, we compared BC samples with normal controls about the expression of PBX1 in various types of cancers, as well as their

Systemic sclerosis (SSc), also known as scleroderma, is an autoimmune disease with multiple system involvement, and pulmonary complications, including pulmonary hypertension (PH), are leading causes of death. This study aimed to develop early biomarkers to distinguish SSc with or without PH from normal population using bioinformatics approaches. The gene expression profile GSE22356, which contains

Metabolic genes have been reported to act as crucial roles in tumor progression. Lung adenocarcinoma (LUAD) is one of the most common cancers worldwide. This study aimed to predict the potential mechanism and novel markers of metabolic signature in LUAD. The gene expression profiles and the clinical parameters were obtained from The Cancer Genome Atlas-Lung adenocarcinoma (TCGA-LUAD) and Gene Expression

Clustered regularly interspaced short palindromic repeats (CRISPR), a class of immune-associated sequences in bacteria, have been developed as a powerful tool for editing eukaryotic genomes in diverse cells and organisms in recent years. The CRISPR-Cas9 system can recognize upstream 20 nucleotides (guide sequence) adjacent to the protospacer-adjacent motif site and trigger double-stranded DNA cleavage

FD-180 and FD-600 are two next-generation sequencing panels developed by First Dimension Biosciences Co. for detecting mutations in cancer tissues and providing therapeutics guidance in precision medicine applications. FD-180 includes the coding exons of about 180 genes, including all the known drug target genes and some important driver genes; whereas FD-600 includes the coding exons of 578 cancer

Melanoma is an extremely malignant and occult tumor. To identify candidate genes related to melanoma carcinogenesis and progression, the microarray data sets GSE83583, GSE130244, and GSE31879 were retrieved from the Gene Expression Omnibus (GEO) database using the GEO2R analytical tool provided by the National Center for Biotechnology Information (NCBI). Gene expression analysis was carried out using

Clinical factors, including T-stage, Gleason score, and baseline prostate-specific antigen, are used to stratify patients with prostate cancer (PCa) into risk groups. This provides prognostic information for a heterogeneous disease such as PCa and guides treatment selection. In this article, we hypothesize that nonclinical factors may also impact treatment selection and their adherence to treatment

The increasing availability of complex data in biology and medicine has promoted the use of machine learning in classification tasks to address important problems in translational and fundamental science. Two important obstacles, however, may limit the unraveling of the full potential of machine learning in these fields: the lack of generalization of the resulting models and the limited number of labeled

Intervertebral disc degeneration (IDD) is the major cause of low back pain. The current study was aimed to further elucidate the mechanisms underlying it. Microarray data sets GSE70362 containing Thompson degeneration grades I–V were divided into the control and the degenerative group and were analyzed. Differentially expressed genes (DEGs) were screened and clustered, followed by functional enrichment

The storage and analysis of massive genetic variation datasets in variant call format (VCF) become a great challenge with the rapid growth of genetic variation data in recent years. Traditional single process based tool kits become increasingly inefficient when analyzing massive genetic variation data. While emerging distributed storage technology such as Apache Kudu offers attractive solution, it

Sequence alignment is a fundamental concept in bioinformatics to distinguish regions of similarity among various sequences. The degree of similarity has been considered as a score. There are a number of various methods to find the statistical significance of similarity in the gapped and ungapped cases. In this article, we improve the statistical significance accuracy of the local score by introducing

We build a theoretical model of morphogenesis. This model describes cell fate in the developing organism using the notion of epigenetic code of each cell. Namely, given the epigenetic spectra of a cell and its neighboring cells, we can determine the corresponding cell event it will perform. This means that the properties of a group of cells (comprising an embryo or its part) at any time point are also

One of the main methods to analyze gene expression data is biclustering, a nonsupervised technique, which consists of selection subgroups of genes that co-expressed under subgroups of experimental conditions. A large number of biclustering algorithms have been developed to classify gene expression data. These algorithms can give as output a large number of overlapped biclusters, whose visualization

This study aimed to explore the similarity between the physical and chemical properties of different acaricides, determine whether Lipinski's Rule of Five (RO5) used in the design of drug molecules is suitable for screening acaricides, and provide methods for selection of new acaricides. We evaluated and predicted the molecular properties of >180 acaricides using Molinspiration. We calculated physicochemical

By using next-generation sequencing technologies, it is possible to quickly and inexpensively generate large numbers of relatively short reads from both the nuclear and mitochondrial DNA (mtDNA) contained in a biological sample. Unfortunately, assembling such whole-genome sequencing (WGS) data with standard de novo assemblers often fails to generate high-quality mitochondrial genome sequences due to

The problem of computing the rooted subtree prune and regraft (rSPR) distance of two phylogenetic trees is computationally hard and so is the problem of computing the hybridization number of two phylogenetic trees (denoted by Hybridization Number Computation [HNC]). Since they are important problems in phylogenetics, they have been studied extensively in the literature. Indeed, quite a number of exact

This study aimed at investigating the crucial mechanisms underlying non-small cell lung cancer (NSCLC). NSCLC-related microarray data GSE27262 were downloaded from Gene Expression Omnibus, including 7 NSCLC 1a samples, 18 NSCLC 1b samples, and their matched normal samples. The common differentially expressed genes (DEGs) between NSCLC 1a and NSCLC 1b samples were identified, followed by protein-protein

Comparison of RNA structures is one of the most crucial analysis for elucidating their individual functions and promoting medical applications. Because it is widely accepted that their functions and structures are strongly correlated, various methods for RNA secondary structure analysis have been proposed owing to the difficulty in predicting RNA three-dimensional structure directly from its sequence

The expression of genes is inevitably subject to intracellular noise. Noise, for some regulatory networks, is constructive but detrimental to many others. The intensity of the noise is a determinant factor and the method of tuning it is of great value. In this study, we illustrated that the transcriptional delay in an incoherent feedforward loop (FFL) grants the target protein modulation the intensity

The dendritic spines play a crucial role in learning and memory processes, epileptogenesis, drug addiction, and postinjury recovery. The shape of the dendritic spine is a morphological key to understand learning and memory process. The classification of the dendritic spines is based on their shapes but the major questions are how the shapes changes in time, how the synaptic strength changes, and is

Current work for multivariate analysis of phenotypes in genome-wide association studies often requires that genetic similarity matrices be inverted or decomposed. This can be a computational bottleneck when many phenotypes are presented, each with a different missingness pattern. A usual method in this case is to perform decompositions on subsets of the kinship matrix for each phenotype, with each

Precision medicine has become a trend in the field of biomedical research. Analysis of mRNA and microRNA (miRNA) is a basis of it. Although the analyses of mRNA and miRNA in different cancers have been studied widely, only a few integrated studies concerning their interactions on large patient cohorts have been done. In this article, we study the integrated significance of mRNA, miRNA, and their interactions

Although the incidence of thyroid carcinoma is reported to be the highest among malignancies of endocrine system, its diagnosis is still unsatisfactory. This study sought to explore the key DNA methylation-driven genes in the development of papillary thyroid carcinoma (PTC) via a bioinformatic analysis based on the Cancer Genome Atlas (TCGA) database and was validated using the Gene Expression Omnibus

The multiomics data are heterogeneous and come from different biological levels such as epigenetics, genomics, transcriptomics and proteomics. The development of high-throughput technologies has enabled researchers not only to study all the entities together but also to utilize information from different levels spanning DNA methylation, copy number variation (CNV), mutation, gene expression, and miRNA

Complex genomic structural variants (CGSVs) are abnormalities that present with three or more breakpoints, making their discovery a challenge. The majority of existing algorithms for structural variant detection are only designed to find simple structural variants (SSVs) such as deletions and inversions; they fail to find more complex events such as deletion–inversions or deletion–duplications, for

Computational tools used for genomic analyses are becoming more accurate but also increasingly sophisticated and complex. This introduces a new problem in that these pieces of software have a large number of tunable parameters that often have a large influence on the results that are reported. We quantify the impact of parameter choice on transcript assembly and take some first steps toward generating

Single-cell transcriptomics offers a tool to study the diversity of cell phenotypes through snapshots of the abundance of mRNA in individual cells. Often there is additional information available besides the single-cell gene expression counts, such as bulk transcriptome data from the same tissue, or quantification of surface protein levels from the same cells. In this study, we propose models based

Recent in situ multiplexed profiling techniques provide insight into microenvironment formation, maintenance, and transformation through a lens of localized cellular phenotype distribution. In this article, we introduce a method for recovering signatures of microenvironments from such data. We use topic models to identify characteristic cell types overrepresented in neighborhoods that serve as proxies

In many application domains, neural networks are highly accurate and have been deployed at large scale. However, users often do not have good tools for understanding how these models arrive at their predictions. This has hindered adoption in fields such as the life and medical sciences, where researchers require that models base their decisions on underlying biological phenomena rather than peculiarities

RNA sequencing (RNA-seq) is widely used to study gene-, transcript-, or exon expression. To quantify the expression level, millions of short sequenced reads need to be mapped back to a reference genome or transcriptome. Read mapping makes it possible to find a location to which a read is identical or similar. Based upon this alignment, expression summaries, that is, read counts are generated. However

The DNA sequencing process has evolved rapidly due to the development of new technologies and equipment capable of producing large amounts of sequencing data. Among these methods, PacBio stands out. The PacBio method uses single molecule real-time, generating sequence files composed by long reads. Storage and analysis of the data generated became a challenge ushering in the development of bioinformatic

Schizophrenia (SZ) is a disease that causes mental disability and affects 1% of the total population in the world. Our aim was to identify new molecular targets that would help to diagnose and treat these patients. The GSE54578 microRNA expression profile was downloaded from the Gene Expression Omnibus database that consists of peripheral blood samples of 15 first-onset SZ patients and 15 healthy controls

The IDH1 mutation is the most frequent somatic mutation in gliomas, and it has an important impact on the treatment outcome of gliomas. Clinically, the gold standard methods for the IDH mutation detection are the immunohistochemistry and gene sequencing techniques, whereas using the histopathology images of the glioma tissues for IDH mutation identification has not been reported. In this study, we

Genome-wide gene expression data for cell model of Parkinson's disease (PD) have considerably improved our understanding of the underlying molecular mechanisms involved in cell death during PD neurodegeneration. Apomorphine (APOM), a nonselective dopamine agonist, has been used to treat patients with advanced PD showing no response to levodopa or other dopamine agonists. Although APOM plays a role

High-dimensional mass cytometry (Cytometry by Time-Of-Flight; CyTOF) is a multiparametric single-cell approach that allows for more than 40 parameters to be evaluated simultaneously, opening the possibility to dissect cellular heterogeneity and elucidate functional interactions between different cell types. However, the complexity of these data makes analysis and interpretation daunting. We created

Colorectal cancer (CRC) is a heterogeneous disease with distinct molecular properties. Tremendous works for CRC molecular subtyping are mainly based on gene expression profiling, which cannot capture the complementary information from other data types. Based on the classical multiomics data integration method similarity network fusion (SNF), which, however, suffers the trivial parameters setting, we

This study was designed to identify several key genes and their functions in preventing or ameliorating intestinal ischemia–reperfusion (IR) injury, which could provide rationale for further exploring the regulatory mechanisms or clinical treatment for intestinal IR injury. The microarray GSE37013 of human intestinal IR injury was downloaded from Gene Expression Omnibus database. The differentially

To explore possible approaches to differentiating rat bone marrow mesenchymal stem cells (BMSCs) into retinal ganglion-like cells and to demonstrate the dynamic changes in protein expression profiles of BMSCs throughout the differentiation. BMSCs were isolated from adult rats and cultured in medium conditioned by neonatal rat retinal cells to induce BMSC differentiation into retinal ganglion-like cells

Multiple transcription factors (TFs) bind to specific sites in the genome and interact among themselves to form the cis-regulatory modules (CRMs). They are essential in modulating the expression of genes, and it is important to study this interplay to understand gene regulation. In the present study, we integrated experimentally identified TF binding sites collected from published studies with computationally

Proper evaluation of the relevant clinical factors for the prognosis of breast cancer is particularly important in the selection of appropriate therapeutic strategies. To further screen and identify the clinically significant factors associated with breast cancer, the Cox risk regression model analysis was performed in this study. The follow-up data of intact breast cancer patients were downloaded

Triple-negative breast cancer is the leading worldwide cause of cancer-related deaths in women. The prospection and development of new substances with antitumoral potential is of great importance for the treatment of this disease. The objective of this work was to identify a commercial drug or ligand that could potentially bind to the FZD7 transmembrane protein and inactivate the Wnt signaling pathway

Single-cell RNA-seq has inspired new discoveries and innovation in the field of developmental and cell biology for the past few years and is useful for studying cellular responses at individual cell resolution. But, due to the paucity of starting RNA, the data acquired have dropouts. To address this, we propose a deep matrix factorization-based method, deepMc, to impute missing values in gene expression

Environmental pollution has emerged to be a major hazard in today's world. Pollutants from varied sources cause harmful effects to the ecosystem. The major pollutants across marine and terrestrial regions are hydrocarbons, plastics, and dyes. Conventional methods for remediation have their own limitations and shortcomings to deal with these environmental pollutants. Bio-based remediation techniques

This study aimed at exploring the genes that may be related to the prognosis of primary breast cancer (BC) patients. The gene expression microarray data, together with sample survival data were acquired from The Cancer Genome Atlas database. The top 20% genes according to expression value variance were subjected to hierarchical cluster analysis. Bootstrap methods were utilized to assess the stability

The early diagnosis of lung squamous cell carcinoma (LUSC) is difficult, causing an unsatisfactory prognosis. Therefore, the 5-year survival rate of LUSC is poor. This study aimed at screening the potential diagnostic and prognostic markers for LUSC. The data of LUSC gene expression profiles and DNA methylation were obtained from The Cancer Genome Atlas (TCGA) database; the differentially expressed

Breast cancer is a heterogeneous disease highly diverse in different subtypes, including hormone receptor positive and hormone receptor negative subtypes with variable malignancy, therapy regimen, and different prognosis. In this study, we develop a hormone receptor-specific mRNA–miRNA–lncRNA ceRNA network to identify whether several RNAs play fundamental roles in development and metastasis of breast

This study aimed to assess mRNA and lncRNA expression differences between lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). Cancer tissues were obtained from three LUSC and three LUAD patients, followed by RNA-seq. Differentially expressed mRNAs (DE-mRNAs) and lncRNAs (DE-lncRNAs) were identified between LUSC and LUAD, after which functional enrichment analysis and protein–protein

Pancreatic cancer (PC) whose mortality is comparable to morbidity is a highly fatal disease. Early approaches of diagnosis and treatment for PC are quite limited, so it is of great urgency to figure out the exact tumorigenesis and development mechanism of PC. To identify the related molecular markers of pancreatic oncogenesis, we downloaded three microarray datasets (GSE63111, GSE101448, and GSE107610)

RHOJ is a small G protein characterized by its abundant expression in endothelial cells. Existing research has documented a link between abnormal RHOJ expression and carcinogenesis. This research aims to investigate the protective role of RHOJ in nonsmall cell lung cancer (NSCLC). In this study, Cancer Genome Atlas database and Gene Expression Omnibus were collected to analyze RHOJ expression and gene

We aimed to identify critical genes for metastasis and prognosis of high-grade serous ovarian cancer (HGSOC). The mRNA data of GSE73064 including 15 HGSOC samples (5 primary tumor cells, 5 ascites tumor cells, and 5 metastasis tumor cells) were applied for the present analysis. The data were first preprocessed using robust multiarray average (RMA) method, and time-series gene expression analyses were

Hirschsprung's disease (HSCR) is a common newborn defect. This study aimed to identify critical genes involved in the development of HSCR. Differently expressed genes (DEGs) of public data set GSE98502 were analyzed using paired t-test. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using Database for Annotation, Visualization and Integrated

For many types of high-throughput sequencing experiments, success in downstream analysis depends on attaining sufficient coverage for individual positions in the genome. For example, when identifying single-nucleotide variants de novo, the number of reads supporting a particular variant call determines our confidence in that variant call. If sequenced reads are distributed uniformly along the genome

Poisson–Nernst–Planck (PNP) model has been extensively used for the study of channel flow under the influence of electrochemical gradients. PNP theory is a continuum description of ion flow where ionic distributions are described in terms of concentrations. Nonionic interparticle interactions are not considered in this theory as in continuum framework, their impact on the solution is minimal. This

The transcriptome of a tumor contains detailed information about the disease. Although advances in sequencing technologies have generated larger data sets, there are still many questions about exactly how the transcriptome is regulated. One class of regulatory elements consists of microRNAs (or miRs), many of which are known to be associated with cancer. To better understand the relationships between

Logistic regression is an effective tool in case–control analysis. With the advanced high throughput technology, a quest to seek a fast and efficient method in fitting high-dimensional logistic regression has gained much interest. An empirical Bayes model for logistic regression is considered in this article. A spike-and-slab prior is used for variable selection purpose, which plays a vital role in

Genomic selection is a modified form of marker-assisted selection in which the markers from the whole genome are used to estimate the genomic-estimated breeding value (GEBV). Several estimators are available to estimate GEBV. These estimators are able to capture either additive genetic effects or nonadditive genetic effects. However, there is hardly any procedure available that could capture both the

Genome-scale metabolic models have been proven to be valuable for defining cancer or to indicate the severity of cancer. However, identifying effective metabolic drug target (DT) of the active small-molecule compound is difficult to unravel and needs to be investigated. In this study, we identify effective DT for breast cancer using proposed network analysis of enzyme-centric network in the metabolic