Current Bioinformatics - Volume 15, Issue 8, 2020

This study focused on describing the necessary information related to pathway mechanisms, characteristics, and databases feature annotations. Various difficulties related to data storage and retrieval in biological pathway databases are discussed. These focus on different techniques for retrieving annotations, features, and methods of digital pathway databases for biological pathway analysis. Furthermore, many pathway Read More

Proteins are large molecules consisting of a linear sequence of amino acids. Protein performs biological functions with specific 3D structures. The main factors that drive proteins to form these structures are constraint between residues. These constraints usually lead to important inter-residue relationships, including short-range inter-residue contacts and long-range interresidue distances. Thus, a highly accurate prediction of in Read More

In this work, a review of predicting lncRNA-protein interactions by bioinformatics methods is provided with a focus on machine learning. Firstly, a computational framework for predicting lncRNA-protein interactions is presented. Then, the currently available data resources for the predictions have been listed. The existing methods will be reviewed by introducing their crucial steps in the prediction framework. The key functions Read More

Background: The utilization of genetic data to investigate biological problems has recently become a vital approach. However, it is undeniable that the heterogeneity of original samples at the biological level is usually ignored when utilizing genetic data. Different cell-constitutions of a sample could differentiate the expression profile, and set considerable biases for downstream research. Matrix factorization (MF) which originat Read More

Throughout the central nervous system (CNS), the information communicated between neurons is mainly implemented by the action potentials (or spikes). Although the spike-timing based neuronal codes have significant computational advantages over rate encoding scheme, the exact spike timing-based learning mechanism in the brain remains an open question. To close this gap, many weight-based supervised learning algo Read More

The segmentation of multiple abdominal organs of the human body from images with different modalities is challenging because of the inter-subject variance among abdomens, as well as the complex intra-subject variance among organs. In this paper, the recent methods proposed for abdominal multi-organ segmentation (AMOS) on medical images in the literature are reviewed. The AMOS methods can be categorized i Read More

Background: T lymphocyte achieves an immune response by recognizing antigen peptides (also known as T cell epitopes) through major histocompatibility complex (MHC) molecules. The immunogenicity of T cell epitopes depends on their source and stability in combination with MHC molecules. The binding of the peptide to MHC is the most selective step, so predicting the binding affinity of the peptide to MHC is the pri Read More

Background: Sunflower (Helianthus annuus L.) is an important oil crop only after soybean, canola and peanuts. A high-quality genetic map is the foundation of marker-assisted selection (MAS). However, for this species, the high-density maps have been reported limitedly. Objective: In this study, we proposed the construction of a high-density genetic linkage map by the F7 population of sunflowers using SNP and SSR Marker Read More

Rapid advances in biological research over recent years have significantly enriched biological and medical data resources. Deep learning-based techniques have been successfully utilized to process data in this field, and they have exhibited state-of-the-art performances even on high-dimensional, nonstructural, and black-box biological data. The aim of the current study is to provide an overview of the deep learning-ba Read More

Background: There have been rapid developments in various bioinformatics technologies, which have led to the accumulation of a large amount of biomedical data. However, these datasets usually involve thousands of features and include much irrelevant or redundant information, which leads to confusion during diagnosis. Feature selection is a solution that consists of finding the optimal subset, which is known to be an NP probl Read More

Background: Drought is one of the most damaging and widespread abiotic stresses that can severely limit the rice production. MicroRNAs (miRNAs) act as a promising tool for improving the drought tolerance of rice and have become a hot spot in recent years. Objective: In order to further extend the understanding of miRNAs, the functions of miRNAs in rice under drought stress are analyzed by bioinformatics. Methods: In t Read More

Background: Among all the major post-translational modifications, amidation seems to be a small change, where a peptide ends with an amide group (-NH 2), not a carboxyl group (-COOH). Thus, to study their physicochemical properties, identification of the amidation mechanism is very important. However, the in vitro, ex vivo and in vivo identification can be laborious, time-taking and costly. There is a dire need for an eff Read More

Background: De novo peptide sequencing is one of the key technologies in proteomics, which can extract peptide sequences directly from tandem mass spectrometry (MS/MS) spectra without any protein databases. Since the accuracy and efficiency of de novo peptide sequencing can be affected by the quality of the MS/MS data, the DeepNovo method using deep learning for de novo peptide sequencing is introduced, whi Read More