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Briefings in Bioinformatics

Igor F Tsigelny
Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many cases, one drug cannot target all necessary points of intervention. For example, in cancer therapy, a physician often meets a patient having a genomic profile including more than five molecular aberrations. Drug combination therapy has been an area of interest for a while, for example the classical work of Loewe devoted to the synergism of drugs was published in 1928-and it is still used in calculations for optimal drug combinations...
February 9, 2018: Briefings in Bioinformatics
Ming Hao, Stephen H Bryant, Yanli Wang
While novel technologies such as high-throughput screening have advanced together with significant investment by pharmaceutical companies during the past decades, the success rate for drug development has not yet been improved prompting researchers looking for new strategies of drug discovery. Drug repositioning is a potential approach to solve this dilemma. However, experimental identification and validation of potential drug targets encoded by the human genome is both costly and time-consuming. Therefore, effective computational approaches have been proposed to facilitate drug repositioning, which have proved to be successful in drug discovery...
February 6, 2018: Briefings in Bioinformatics
Shasha Li, Shuaishuai Teng, Junquan Xu, Guannan Su, Yu Zhang, Jianqing Zhao, Suwei Zhang, Haiyan Wang, Wenyan Qin, Zhi John Lu, Yong Guo, Qianyong Zhu, Dong Wang
Circular RNAs (circRNAs) are emerging as a new class of endogenous and regulatory noncoding RNAs in latest years. With the widespread application of RNA sequencing (RNA-seq) technology and bioinformatics prediction, large numbers of circRNAs have been identified. However, at present, we lack a comprehensive characterization of all these circRNAs in interested samples. In this study, we integrated 87 935 circRNAs sequences that cover most of circRNAs identified till now represented in circBase to design microarray probes targeting back-splice site of each circRNA to profile expression of those circRNAs...
February 3, 2018: Briefings in Bioinformatics
Junpeng Zhang, Thuc Duy Le, Lin Liu, Jiuyong Li
It is known that noncoding RNAs (ncRNAs) cover ∼98% of the transcriptome, but do not encode proteins. Among ncRNAs, long noncoding RNAs (lncRNAs) are a large and diverse class of RNA molecules, and are thought to be a gold mine of potential oncogenes, anti-oncogenes and new biomarkers. Although only a minority of lncRNAs is functionally characterized, it is clear that they are important regulators to modulate gene expression and involve in many biological functions. To reveal the functions and regulatory mechanisms of lncRNAs, it is vital to understand how lncRNAs regulate their target genes for implementing specific biological functions...
February 1, 2018: Briefings in Bioinformatics
Andrés Zalguizuri, Gustavo Caetano-Anollés, Viviana Claudia Lepek
In the establishment and maintenance of the interaction between pathogenic or symbiotic bacteria with a eukaryotic organism, protein substrates of specialized bacterial secretion systems called effectors play a critical role once translocated into the host cell. Proteins are also secreted to the extracellular medium by free-living bacteria or directly injected into other competing organisms to hinder or kill. In this work, we explore an approach based on the evolutionary dependence that most of the effectors maintain with their specific secretion system that analyzes the co-occurrence of any orthologous protein group and their corresponding secretion system across multiple genomes...
January 31, 2018: Briefings in Bioinformatics
Alessandra Dal Molin, Barbara Di Camillo
The sequencing of the transcriptome of single cells, or single-cell RNA-sequencing, has now become the dominant technology for the identification of novel cell types in heterogeneous cell populations or for the study of stochastic gene expression. In recent years, various experimental methods and computational tools for analysing single-cell RNA-sequencing data have been proposed. However, most of them are tailored to different experimental designs or biological questions, and in many cases, their performance has not been benchmarked yet, thus increasing the difficulty for a researcher to choose the optimal single-cell transcriptome sequencing (scRNA-seq) experiment and analysis workflow...
January 31, 2018: Briefings in Bioinformatics
Paul Medvedev
As computer scientists working in bioinformatics/computational biology, we often face the challenge of coming up with an algorithm to answer a biological question. This occurs in many areas, such as variant calling, alignment and assembly. In this tutorial, we use the example of the genome assembly problem to demonstrate how to go from a question in the biological realm to a solution in the computer science realm. We show the modeling process step-by-step, including all the intermediate failed attempts. Please note this is not an introduction to how genome assembly algorithms work and, if treated as such, would be incomplete and unnecessarily long-winded...
January 30, 2018: Briefings in Bioinformatics
Fernando Carazo, Juan P Romero, Angel Rubio
Alternative splicing (AS) has shown to play a pivotal role in the development of diseases, including cancer. Specifically, all the hallmarks of cancer (angiogenesis, cell immortality, avoiding immune system response, etc.) are found to have a counterpart in aberrant splicing of key genes. Identifying the context-specific regulators of splicing provides valuable information to find new biomarkers, as well as to define alternative therapeutic strategies. The computational models to identify these regulators are not trivial and require three conceptual steps: the detection of AS events, the identification of splicing factors that potentially regulate these events and the contextualization of these pieces of information for a specific experiment...
January 29, 2018: Briefings in Bioinformatics
Ali Ezzat, Min Wu, Xiao-Li Li, Chee-Keong Kwoh
Computational prediction of drug-target interactions (DTIs) has become an essential task in the drug discovery process. It narrows down the search space for interactions by suggesting potential interaction candidates for validation via wet-lab experiments that are well known to be expensive and time-consuming. In this article, we aim to provide a comprehensive overview and empirical evaluation on the computational DTI prediction techniques, to act as a guide and reference for our fellow researchers. Specifically, we first describe the data used in such computational DTI prediction efforts...
January 24, 2018: Briefings in Bioinformatics
Florencio Pazos, Monica Chagoyen
Daily work in molecular biology presently depends on a large number of computational tools. An in-depth, large-scale study of that 'ecosystem' of Web tools, its characteristics, interconnectivity, patterns of usage/citation, temporal evolution and rate of decay is crucial for understanding the forces that shape it and for informing initiatives aimed at its funding, long-term maintenance and improvement. In particular, the long-term maintenance of these tools is compromised because of their specific development model...
January 16, 2018: Briefings in Bioinformatics
Hao Luo, Chun-Lan Quan, Chong Peng, Feng Gao
DNA replication begins at replication origins in all three domains of life. Identification and characterization of replication origins are important not only in providing insights into the structure and function of the replication origins but also in understanding the regulatory mechanisms of the initiation step in DNA replication. The Z-curve method has been used in the identification of replication origins in archaeal genomes successfully since 2002. Furthermore, the Web servers of Ori-Finder and Ori-Finder 2 have been developed to predict replication origins in both bacterial and archaeal genomes based on the Z-curve method, and the replication origins with manual curation have been collected into an online database, DoriC...
January 9, 2018: Briefings in Bioinformatics
Qin Tang, Qiong Zhang, Yao Lv, Ya-Ru Miao, An-Yuan Guo
Human specifically expressed genes (SEGs) usually serve as potential biomarkers for disease diagnosis and treatment. However, the regulation underlying their specific expression remains to be revealed. In this study, we constructed SEG regulation database (SEGreg; available at for showing SEGs and their transcription factors (TFs) and microRNA (miRNA) regulations under different physiological conditions, which include normal tissue, cancer tissue and cell line. In total, SEGreg collected 6387, 1451, 4506 and 5320 SEGs from expression profiles of 34 cancer types and 55 tissues of The Cancer Genome Atlas, Cancer Cell Line Encyclopedia, Human Body Map and Genotype-Tissue Expression databases/projects, respectively...
January 3, 2018: Briefings in Bioinformatics
Rajeev K Azad, Vladimir Shulaev
Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment...
January 3, 2018: Briefings in Bioinformatics
Yongjun Zhu, Olivier Elemento, Jyotishman Pathak, Fei Wang
Recent advances in biomedical research have generated a large volume of drug-related data. To effectively handle this flood of data, many initiatives have been taken to help researchers make good use of them. As the results of these initiatives, many drug knowledge bases have been constructed. They range from simple ones with specific focuses to comprehensive ones that contain information on almost every aspect of a drug. These curated drug knowledge bases have made significant contributions to the development of efficient and effective health information technologies for better health-care service delivery...
January 3, 2018: Briefings in Bioinformatics
Ruiping Wang, Yue Han, Zhangxiang Zhao, Fan Yang, Tingting Chen, Wenbin Zhou, Xianlong Wang, Lishuang Qi, Wenyuan Zhao, Zheng Guo, Yunyan Gu
Synthetic lethal (SL) interactions occur when alterations in two genes lead to cell death but alteration in only one of them is not lethal. SL interactions provide a new strategy for molecular-targeted cancer therapy. Currently, there are few drugs targeting SL interactions that entered into clinical trials. Therefore, it is necessary to investigate the link between SL interactions and drug sensitivity of cancer cells systematically for drug development purpose. We identified SL interactions by integrating the high-throughput data from The Cancer Genome Atlas, small hairpin RNA data and genetic interactions of yeast...
December 28, 2017: Briefings in Bioinformatics
Bin Liu
With the avalanche of biological sequences generated in the post-genomic age, one of the most challenging problems is how to computationally analyze their structures and functions. Machine learning techniques are playing key roles in this field. Typically, predictors based on machine learning techniques contain three main steps: feature extraction, predictor construction and performance evaluation. Although several Web servers and stand-alone tools have been developed to facilitate the biological sequence analysis, they only focus on individual step...
December 19, 2017: Briefings in Bioinformatics
Giulia Tini, Luca Marchetti, Corrado Priami, Marie-Pier Scott-Boyer
With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work, the impact of these factors is explored when solving the problem of sample classification, by comparing the performances of five unsupervised algorithms: Multiple Canonical Correlation Analysis, Multiple Co-Inertia Analysis, Multiple Factor Analysis, Joint and Individual Variation Explained and Similarity Network Fusion...
December 18, 2017: Briefings in Bioinformatics
Francesca Vitali, Qike Li, A Grant Schissler, Joanne Berghout, Colleen Kenost, Yves A Lussier
The development of computational methods capable of analyzing -omics data at the individual level is critical for the success of precision medicine. Although unprecedented opportunities now exist to gather data on an individual's -omics profile ('personalome'), interpreting and extracting meaningful information from single-subject -omics remain underdeveloped, particularly for quantitative non-sequence measurements, including complete transcriptome or proteome expression and metabolite abundance. Conventional bioinformatics approaches have largely been designed for making population-level inferences about 'average' disease processes; thus, they may not adequately capture and describe individual variability...
December 18, 2017: Briefings in Bioinformatics
Jochen Singer, Anja Irmisch, Hans-Joachim Ruscheweyh, Franziska Singer, Nora C Toussaint, Mitchell P Levesque, Daniel J Stekhoven, Niko Beerenwinkel
Molecular profiling of tumor biopsies plays an increasingly important role not only in cancer research, but also in the clinical management of cancer patients. Multi-omics approaches hold the promise of improving diagnostics, prognostics and personalized treatment. To deliver on this promise of precision oncology, appropriate bioinformatics methods for managing, integrating and analyzing large and complex data are necessary. Here, we discuss the specific requirements of bioinformatics methods and software that arise in the setting of clinical oncology, owing to a stricter regulatory environment and the need for rapid, highly reproducible and robust procedures...
December 18, 2017: Briefings in Bioinformatics
Celia W G van Gelder, Rob W W Hooft, Merlijn N van Rijswijk, Linda van den Berg, Ruben G Kok, Marcel Reinders, Barend Mons, Jaap Heringa
No abstract text is available yet for this article.
December 15, 2017: Briefings in Bioinformatics
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