The advancement of single-cell sequencing technology in recent years has provided an opportunity to reconstruct gene regulatory networks (GRNs) with the data from thousands of single cells in one sample. This uncovers regulatory interactions in cells and speeds up the discoveries of regulatory mechanisms in diseases and biological processes. Therefore, more methods have been proposed to reconstruct GRNs using single-cell sequencing data. In this review, we introduce technologies for sequencing single-cell genome, transcriptome, and epigenome.  https://www.selleckchem.com/products/frax597.html  At the same time, we present an overview of current GRN reconstruction strategies utilizing different single-cell sequencing data. Bioinformatics tools were grouped by their input data type and mathematical principles for reader's convenience, and the fundamental mathematics inherent in each group will be discussed. Furthermore, the adaptabilities and limitations of these different methods will also be summarized and compared, with the hope to facilitate researchers recognizing the most suitable tools for them.Circadian rhythms are 24-hour oscillations affecting an organism at multiple levels from gene expression all the way to tissues and organs. They have been observed in organisms across the kingdom of life, spanning from cyanobacteria to humans. In mammals, the master circadian pacemaker is located in the hypothalamic suprachiasmatic nuclei (SCN) in the brain where it synchronizes the peripheral oscillators that exist in other tissues. This system regulates the circadian activity of a large part of the transcriptome and recent findings indicate that almost every cell in the body has this clock at the molecular level. In this review, we briefly summarize the different factors that can influence the circadian transcriptome, including light, temperature, and food intake. We then summarize recently identified general principles governing genome-scale circadian regulation, as well as future lines of research. Genome-scale circadian activity represents a fascinating study model for computational biology. For this purpose, systems biology methods are promising exploratory tools to decode the global regulatory principles of circadian regulation.Chaos Game Representation (CGR) was first proposed to be an image representation method of DNA and have been extended to the case of other biological macromolecules. Compared with the CGR images of DNA, where DNA sequences are converted into a series of points in the unit square, the existing CGR images of protein are not so elegant in geometry and the implications of the distribution of points in the CGR image are not so obvious. In this study, by naturally distributing the twenty amino acids on the vertices of a regular dodecahedron, we introduce a novel three-dimensional image representation of protein sequences with CGR method. We also associate each CGR image with a vector in high dimensional Euclidean space, called the extended natural vector (ENV), in order to analyze the information contained in the CGR images. Based on the results of protein classification and phylogenetic analysis, our method could serve as a precise method to discover biological relationships between proteins.The effective non-invasive diagnosis and prognosis are critical for cancer treatment. The plasma cell-free DNA (cfDNA) provides a good material for cancer liquid biopsy and its worth in this field is increasingly explored. Here we describe a new pipeline for effectively finding new cfDNA-based biomarkers for cancers by combining SALP-seq and machine learning. Using the pipeline, 30 cfDNA samples from 26 esophageal cancer (ESCA) patients and 4 healthy people were analyzed as an example. As a result, 103 epigenetic markers (including 54 genome-wide and 49 promoter markers) and 37 genetic markers were identified for this cancer. These markers provide new biomarkers for ESCA diagnosis, prognosis and therapy. Importantly, these markers, especially epigenetic markers, not only shed important new insights on the regulatory mechanisms of this cancer, but also could be used to classify the cfDNA samples. We therefore developed a new pipeline for effectively finding new cfDNA-based biomarkers for cancers by combining SALP-seq and machine learning. In this study, we also discovered new clinical worth of cfDNA distinct from other reported characters.Pseudouridine synthase binds to uridine sites and catalyzes the conversion of uridine to pseudouridine (Ψ). This binding takes place in a specific context and in the conformation of nucleotides. Most machine-learning methods for Ψ site classification use nucleotide frequency as a feature, which may not fully depict the relevant conformation around a Ψ site. Using the power of deep learning and raw sequence, as well as secondary structure features, our tool MU-PseUDeep is designed to capture both the sequence and secondary structure context, which inputs the raw RNA sequence and the predicted secondary structure to two sets of convolutional neural networks. It has shown considerable improvement in Ψ site prediction over existing tools, XG-PseU, PseUI, and iRNA-PseU for both balanced and imbalanced datasets. To the best of our knowledge, this is the most accurate tool for Ψ site prediction. We also used MU-PseUDeep to scan the human transcriptome, which shows that the genes with predicted Ψ sites are enriched in nucleotide and protein binding, as well as in neurodegeneration pathways. The tool is open source, available at https//github.com/smk5g5/MU-PseUDeep.Fourteen species of scale insects from the families Margarodidae s.l., Pseudococcidae, Eriococcidae, and Coccidae were investigated for the first time in respect to karyotypes, genetic systems, modes of reproduction and general anatomy of the female reproductive system. One of the studied species, Steatococcus samaraius Morrison, 1927, showed hermaphroditic reproduction of the female-like specimens, the other species demonstrated bisexual reproduction with a peculiar "Lecanoid" heterochromatinization of the paternal set of chromosomes in male embryos or thelytocous parthenogenesis. Antonina parazonata Williams, 2004 and Saccharolecanium krugeri (Zehntner, 1897) are recorded here for the first time from Thailand, Antonina vietnamensis Williams, 2004 and Geococcus satellitum Williams, 2004 - for the first time from Laos.