Current Bioinformatics - Volume 13, Issue 4, 2018

Background: Existing alignment-based phylogenetic methods remain computationally arduous and even impossible for large numbers of viral genetic sequences. Objective: Alignment-free methodologies which successfully overcome serious limitations of alignment-based ways, especially for computation time and storage space, have been quickly proposed. Methods: Natural vector method is a new alignment-free approac Read More

Background: In recent years, there is an increasing number of researchers applying bioimaging techniques to generate a myriad of biological images. The growing image data pose great methodological challenges for image processing and quantitative analysis. The analyses of biological images range from the quantification of phenotypes to the visualization of biological structures. Objective: Accurate, high-throughput an Read More

Background: As potent gene regulators, long noncoding RNAs (lncRNAs) are critical in various biological activities, such as cellular processes. With the development of new sequencing technologies, vast amount of transcriptome data are available, which require efficient computational tools to distinguish noncoding RNAs from their coding counterparts, especially for lncRNAs. Methods: In this paper, we review the advancement Read More

Background: Bioinformatics research comes into an era of big data. Mining potential value in biological big data for scientific research and health care field has the vital significance. Deep learning as new machine learning algorithms, on the basis of big data and high performance distributed parallel computing, show the excellent performance in biological big data processing. Objective: Provides a valuable reference for resea Read More

Background: An epidemic can spread rapidly among a large number of people in a community within a short period of time. Some infectious diseases, including influenza, hand, foot and mouth disease, dengue and meningitis, are temporally limited by variations in the meteorological factors, such as sunshine, temperature, humidity, rainfall, atmospheric pressure, wind speed and so on. Therefore, it is necessary to pre Read More

Background: A key goal of mining single nucleotide polymorphism data of complex diseases (CD) is to build models that provide fundamental insight into genetic variations of CD. Therefore, we can predict disease risk and clinical outcomes and ultimately understand the development and progress mechanism of CD. As the technologies of omics data generation and computer science, the reductionist paradigm of genome Read More

Background: Recently, novel high-throughput biotechnologies have provided rich data about different genomes. However, manual annotation of gene function is time consuming. It is also very expensive and infeasible for the growing amounts of data. At present there are numerous functions in certain species that remain unknown or only partially known. Hence, the use of computational approaches to predicting gene function Read More

Background: Post-translational modifications (PTMs) are a key regulating mechanism in the cellular process. It is of importance to quickly and accurately identify PTMs. Both next generation sequencing as well as bioinformatics techniques greatly facilitated discovery of PTMs. Most bioinformatics techniques followed the machine learning framework where feature extraction occupies a key position. Conclusion: The a Read More

Background: Host-parasite protein interactions (HPPI) are those interactions occurring between a parasite and its host. Host-parasite protein interaction enhances the understanding of how parasite can infect its host. The interaction plays an important role in initiating infections, although it is not all host-parasite interactions that result in infection. Identifying the protein-protein interactions (PPIs) that allow a parasite to infe Read More

Background: A central problem of systems biology is the reconstruction of the topology of gene regulatory networks (GRNs) using high throughput genomic data like microarray gene expression data. The main challenge in gene expression data is that the number of genes is high, number of samples is low, and the data are often impregnated with noise. Objective: In this paper, we present a method for Gene Regulatory Netw Read More

Background: Recent studies suggest that the one-dimensional genomic feature, isochore, underlie the three-dimensional chromatin architecture. It has also been reported that open chromatin fibers originate from regions of high gene density while closed chromatin corresponds to low gene density chromosomal regions. Objective: To verify how the 3D architecture of chromatin is linked to the one-dimensional genomic featur Read More

Background: Rapid accumulation of genomic and transcriptomic data initiates the development of computational methods to identify the regulation of transcriptional factors (TF) and genes. However, available methods display high false-positive rate and unstable performance across different networks due to their preferences for interactions with certain features. Model integration can reduce the biases of these methods and i Read More