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Briefings in Bioinformatics

Michiel Stock, Tapio Pahikkala, Antti Airola, Willem Waegeman, Bernard De Baets
Supervised machine learning techniques have traditionally been very successful at reconstructing biological networks, such as protein-ligand interaction, protein-protein interaction and gene regulatory networks. Many supervised techniques for network prediction use linear models on a possibly nonlinear pairwise feature representation of edges. Recently, much emphasis has been placed on the correct evaluation of such supervised models. It is vital to distinguish between using a model to either predict new interactions in a given network or to predict interactions for a new vertex not present in the original network...
October 16, 2018: Briefings in Bioinformatics
Xing Chen, Na-Na Guan, Ya-Zhou Sun, Jian-Qiang Li, Jia Qu
Small molecule is a kind of low molecular weight organic compound with variety of biological functions. Studies have indicated that small molecules can inhibit a specific function of a multifunctional protein or disrupt protein-protein interactions and may have beneficial or detrimental effect against diseases. MicroRNAs (miRNAs) play crucial roles in cellular biology, which makes it possible to develop miRNA as diagnostics and therapeutic targets. Several drug-like compound libraries were screened successfully against different miRNAs in cellular assays further demonstrating the possibility of targeting miRNAs with small molecules...
October 16, 2018: Briefings in Bioinformatics
Martin Siebenhaller, Sune S Nielsen, Fintan McGee, Irina Balaur, Charles Auffray, Alexander Mazein
The use of signalling pathway hypergraphs represented as process description diagrams is steadily becoming more pervasive in the field of biology. This makes ever more evident the necessity for an effective automated layout that can replicate high-quality manually drawn diagrams. The complexity and idiosyncrasies of these diagrams, as well as the specific tasks the end users perform with them, mean that a layout must meet many requirements beyond the simple metrics used in existing automated computational approaches...
October 5, 2018: Briefings in Bioinformatics
Jifan Shi, Andrew E Teschendorff, Weiyan Chen, Luonan Chen, Tiejun Li
MOTIVATION: Estimating differentiation potency of single cells is a task of great biological and clinical significance, as it may allow identification of normal and cancer stem cell phenotypes. However, very few single-cell potency models have been proposed, and their robustness and reliability across independent studies have not yet been fully assessed. RESULTS: Using nine independent single-cell RNA-Seq experiments, we here compare four different single-cell potency models to each other, in their ability to discriminate cells that ought to differ in terms of differentiation potency...
October 5, 2018: Briefings in Bioinformatics
Zhen Chen, Xuhan Liu, Fuyi Li, Chen Li, Tatiana Marquez-Lago, André Leier, Tatsuya Akutsu, Geoffrey I Webb, Dakang Xu, Alexander Ian Smith, Lei Li, Kuo-Chen Chou, Jiangning Song
Lysine post-translational modifications (PTMs) play a crucial role in regulating diverse functions and biological processes of proteins. However, because of the large volumes of sequencing data generated from genome-sequencing projects, systematic identification of different types of lysine PTM substrates and PTM sites in the entire proteome remains a major challenge. In recent years, a number of computational methods for lysine PTM identification have been developed. These methods show high diversity in their core algorithms, features extracted and feature selection techniques and evaluation strategies...
October 4, 2018: Briefings in Bioinformatics
Maciej Blaszczyk, Maciej Pawel Ciemny, Andrzej Kolinski, Mateusz Kurcinski, Sebastian Kmiecik
CABS-dock is a tool for flexible docking of peptides to proteins. In this article, we present a protocol for CABS-dock docking driven by information about protein-peptide contact(s). Using information on individual protein-peptide contacts allows to improve the accuracy of CABS-dock docking.
September 20, 2018: Briefings in Bioinformatics
Quan Zou, Gang Lin, Xingpeng Jiang, Xiangrong Liu, Xiangxiang Zeng
Sequence clustering is a basic bioinformatics task that is attracting renewed attention with the development of metagenomics and microbiomics. The latest sequencing techniques have decreased costs and as a result, massive amounts of DNA/RNA sequences are being produced. The challenge is to cluster the sequence data using stable, quick and accurate methods. For microbiome sequencing data, 16S ribosomal RNA operational taxonomic units are typically used. However, there is often a gap between algorithm developers and bioinformatics users...
September 18, 2018: Briefings in Bioinformatics
Meng Zou, Rui Jin, Kin Fai Au
The intra-tumor heterogeneity is associated with cancer progression and therapeutic resistance, such as in breast cancer. While the existing methods for studying tumor heterogeneity only analyze variant allele frequency (VAF), the genotype of variant is also informative for inferring subclones, which can be detected by long reads or paired-end reads. We developed GenoClone to integrate VAF with the genotype of variant innovatively, so it showed superior performance of inferring the number of subclones, estimating the fractions of subclones and identifying somatic single-nucleotide variants composition of subclones...
September 18, 2018: Briefings in Bioinformatics
Min Li, Hao Gao, Jianxin Wang, Fang-Xiang Wu
Networks have been widely used to model the structure of various biological systems. Currently, a series of approaches have been developed to construct reliable biological networks. However, the ultimate understanding of a biological system is to steer its states to the desired ones by imposing signals. The control process is dominated by the intrinsic structure and the dynamic propagation. To understand the underlying mechanisms behind the life process, the control theory can be applied to biological networks with specific target requirements...
September 18, 2018: Briefings in Bioinformatics
Mark N Read, Kieran Alden, Jon Timmis, Paul S Andrews
Computational and mathematical modelling has become a valuable tool for investigating biological systems. Modelling enables prediction of how biological components interact to deliver system-level properties and extrapolation of biological system performance to contexts and experimental conditions where this is unknown. A model's value hinges on knowing that it faithfully represents the biology under the contexts of use, or clearly ascertaining otherwise and thus motivating further model refinement. These qualities are evaluated through calibration, typically formulated as identifying model parameter values that align model and biological behaviours as measured through a metric applied to both...
September 18, 2018: Briefings in Bioinformatics
Xiaoli Qiang, Chen Zhou, Xiucai Ye, Pu-Feng Du, Ran Su, Leyi Wei
Cell-penetrating peptides (CPPs) have been shown to be a transport vehicle for delivering cargoes into live cells, offering great potential as future therapeutics. It is essential to identify CPPs for better understanding of their functional mechanisms. Machine learning-based methods have recently emerged as a main approach for computational identification of CPPs. However, one of the main challenges and difficulties is to propose an effective feature representation model that sufficiently exploits the inner difference and relevance between CPPs and non-CPPs, in order to improve the predictive performance...
September 17, 2018: Briefings in Bioinformatics
Saurav Mallik, Gabriel J Odom, Zhen Gao, Lissette Gomez, Xi Chen, Lily Wang
Epigenome-wide association studies (EWASs) have become increasingly popular for studying DNA methylation (DNAm) variations in complex diseases. The Illumina methylation arrays provide an economical, high-throughput and comprehensive platform for measuring methylation status in EWASs. A number of software tools have been developed for identifying disease-associated differentially methylated regions (DMRs) in the epigenome. However, in practice, we found these tools typically had multiple parameter settings that needed to be specified and the performance of the software tools under different parameters was often unclear...
September 17, 2018: Briefings in Bioinformatics
Fentaw Abegaz, Kridsadakorn Chaichoompu, Emmanuelle Génin, David W Fardo, Inke R König, Jestinah M Mahachie John, Kristel Van Steen
Principal components (PCs) are widely used in statistics and refer to a relatively small number of uncorrelated variables derived from an initial pool of variables, while explaining as much of the total variance as possible. Also in statistical genetics, principal component analysis (PCA) is a popular technique. To achieve optimal results, a thorough understanding about the different implementations of PCA is required and their impact on study results, compared to alternative approaches. In this review, we focus on the possibilities, limitations and role of PCs in ancestry prediction, genome-wide association studies, rare variants analyses, imputation strategies, meta-analysis and epistasis detection...
September 14, 2018: Briefings in Bioinformatics
Zhiyu Hao, Li Jiang, Jin Gao, Jinhua Ye, Jingli Zhao, Shuling Li, Runqing Yang
Standard normal statistics, chi-squared statistics, Student's t statistics and F statistics are used to map quantitative trait nucleotides for both small and large sample sizes. In genome-wide association studies (GWASs) of single-nucleotide polymorphisms (SNPs), the statistical distributions depend on both genetic effects and SNPs but are independent of SNPs under the null hypothesis of no genetic effects. Therefore, hypothesis testing when a nuisance parameter is present only under the alternative was introduced to quickly approximate the critical thresholds of these test statistics for GWASs...
September 14, 2018: Briefings in Bioinformatics
Wan-Yu Lin, Ching-Chieh Huang, Yu-Li Liu, Shih-Jen Tsai, Po-Hsiu Kuo
The exploration of 'gene-environment interactions' (G × E) is important for disease prediction and prevention. The scientific community usually uses external information to construct a genetic risk score (GRS), and then tests the interaction between this GRS and an environmental factor (E). However, external genome-wide association studies (GWAS) are not always available, especially for non-Caucasian ethnicity. Although GRS is an analysis tool to detect G × E in GWAS, its performance remains unclear when there is no external information...
September 13, 2018: Briefings in Bioinformatics
Zhidong Tang, Xuecang Li, Jianmei Zhao, Fengcui Qian, Chenchen Feng, Yanyu Li, Jian Zhang, Yong Jiang, Yongsan Yang, Qiuyu Wang, Chunquan Li
In recent years, high-throughput genomic technologies like chromatin immunoprecipitation sequencing (ChIp-seq) and transcriptome sequencing (RNA-seq) have been becoming both more refined and less expensive, making them more accessible. Many circular RNAs (circRNAs) that originate from back-spliced exons have been identified in various cell lines across different species. However, the regulatory mechanism for transcription of circRNAs remains unclear. Therefore, there is an urgent need to construct a database detailing the transcriptional regulation of circRNAs...
September 3, 2018: Briefings in Bioinformatics
Hongyan Yin, Mengwei Li, Lin Xia, Chaozu He, Zhang Zhang
Genes originate at different evolutionary time scales and possess different ages, accordingly presenting diverse functional characteristics and reflecting distinct adaptive evolutionary innovations. In the past decades, progresses have been made in gene age identification by a variety of methods that are principally based on comparative genomics. Here we summarize methods for computational determination of gene age and evaluate the effectiveness of different computational methods for age identification. Our results show that improved age determination can be achieved by combining homolog clustering with phylogeny inference, which enables more accurate age identification in human genes...
September 3, 2018: Briefings in Bioinformatics
Fulong Yu, Fei Quan, Jinyuan Xu, Yan Zhang, Yi Xie, Jingyu Zhang, Yujia Lan, Huating Yuan, Hongyi Zhang, Shujun Cheng, Yun Xiao, Xia Li
Breast cancer is a very complex and heterogeneous disease with variable molecular mechanisms of carcinogenesis and clinical behaviors. The identification of prognostic risk factors may enable effective diagnosis and treatment of breast cancer. In particular, numerous gene-expression-based prognostic signatures were developed and some of them have already been applied into clinical trials and practice. In this study, we summarized several representative gene-expression-based signatures with significant prognostic value and separately assessed their ability of prognosis prediction in their originally targeted populations of breast cancer...
September 3, 2018: Briefings in Bioinformatics
Misagh Naderi, Jeffrey Mitchell Lemoine, Rajiv Gandhi Govindaraj, Omar Zade Kana, Wei Pan Feinstein, Michal Brylinski
Interactions between proteins and small molecules are critical for biological functions. These interactions often occur in small cavities within protein structures, known as ligand-binding pockets. Understanding the physicochemical qualities of binding pockets is essential to improve not only our basic knowledge of biological systems, but also drug development procedures. In order to quantify similarities among pockets in terms of their geometries and chemical properties, either bound ligands can be compared to one another or binding sites can be matched directly...
August 31, 2018: Briefings in Bioinformatics
Fuyi Li, Yanan Wang, Chen Li, Tatiana T Marquez-Lago, André Leier, Neil D Rawlings, Gholamreza Haffari, Jerico Revote, Tatsuya Akutsu, Kuo-Chen Chou, Anthony W Purcell, Robert N Pike, Geoffrey I Webb, A Ian Smith, Trevor Lithgow, Roger J Daly, James C Whisstock, Jiangning Song
The roles of proteolytic cleavage have been intensively investigated and discussed during the past two decades. This irreversible chemical process has been frequently reported to influence a number of crucial biological processes (BPs), such as cell cycle, protein regulation and inflammation. A number of advanced studies have been published aiming at deciphering the mechanisms of proteolytic cleavage. Given its significance and the large number of functionally enriched substrates targeted by specific proteases, many computational approaches have been established for accurate prediction of protease-specific substrates and their cleavage sites...
August 29, 2018: Briefings in Bioinformatics
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