keyword
MENU ▼
Read by QxMD icon Read
search

Bioinformatics & Computational Biology

keyword
https://www.readbyqxmd.com/read/29344895/bioinformatics-approaches-to-predict-drug-responses-from-genomic-sequencing
#1
Neel S Madhukar, Olivier Elemento
Fulfilling the promises of precision medicine will depend on our ability to create patient-specific treatment regimens. Therefore, being able to translate genomic sequencing into predicting how a patient will respond to a given drug is critical. In this chapter, we review common bioinformatics approaches that aim to use sequencing data to predict sample-specific drug susceptibility. First, we explain the importance of customized drug regimens to the future of medical care. Second, we discuss the different public databases and community efforts that can be leveraged to develop new methods for identifying new predictive biomarkers...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29344888/perseus-a-bioinformatics-platform-for-integrative-analysis-of-proteomics-data-in-cancer-research
#2
Stefka Tyanova, Juergen Cox
Mass spectrometry-based proteomics is a continuously growing field marked by technological and methodological improvements. Cancer proteomics is aimed at pursuing goals such as accurate diagnosis, patient stratification, and biomarker discovery, relying on the richness of information of quantitative proteome profiles. Translating these high-dimensional data into biological findings of clinical importance necessitates the use of robust and powerful computational tools and methods. In this chapter, we provide a detailed description of standard analysis steps for a clinical proteomics dataset performed in Perseus, a software for functional analysis of large-scale quantitative omics data...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29335913/analyzing-the-interactions-of-mrnas-mirnas-lncrnas-and-circrnas-to-predict-competing-endogenous-rna-networks-in-glioblastoma
#3
Yang Yuan, Li Jiaoming, Wang Xiang, Liu Yanhui, Jiang Shu, Gou Maling, Mao Qing
Cross-talk between competitive endogenous RNAs (ceRNAs) may play a critical role in revealing potential mechanisms of tumor development and physiology. Glioblastoma is the most common type of malignant primary brain tumor, and the mechanisms of tumor genesis and development in glioblastoma are unclear. Here, to investigate the role of non-coding RNAs and the ceRNA network in glioblastoma, we performed paired-end RNA sequencing and microarray analyses to obtain the expression profiles of mRNAs, lncRNAs, circRNAs and miRNAs...
January 15, 2018: Journal of Neuro-oncology
https://www.readbyqxmd.com/read/29334891/tuning-iteration-space-slicing-based-tiled-multi-core-code-implementing-nussinov-s-rna-folding
#4
Marek Palkowski, Wlodzimierz Bielecki
BACKGROUND: RNA folding is an ongoing compute-intensive task of bioinformatics. Parallelization and improving code locality for this kind of algorithms is one of the most relevant areas in computational biology. Fortunately, RNA secondary structure approaches, such as Nussinov's recurrence, involve mathematical operations over affine control loops whose iteration space can be represented by the polyhedral model. This allows us to apply powerful polyhedral compilation techniques based on the transitive closure of dependence graphs to generate parallel tiled code implementing Nussinov's RNA folding...
January 15, 2018: BMC Bioinformatics
https://www.readbyqxmd.com/read/29328442/identification-of-differentially-expressed-genes-and-regulatory-relationships-in-huntington-s-disease-by-bioinformatics-analysis
#5
Xiaoyu Dong, Shuyan Cong
Huntington's disease (HD) is an inherited, progressive neurodegenerative disease caused by a CAG expansion in the huntingtin (HTT) gene; various dysfunctions of biological processes in HD have been proposed. However, at present the exact pathogenesis of HD is not fully understood. The present study aimed to explore the pathogenesis of HD using a computational bioinformatics analysis of gene expression. GSE11358 was downloaded from the Gene Expression Omnibus andthe differentially expressed genes (DEGs) in the mutant HTT knock‑in cell model STHdhQ111/Q111 were predicted...
January 9, 2018: Molecular Medicine Reports
https://www.readbyqxmd.com/read/29324777/assessing-an-effective-undergraduate-module-teaching-applied-bioinformatics-to-biology-students
#6
Andreas Madlung
Applied bioinformatics skills are becoming ever more indispensable for biologists, yet incorporation of these skills into the undergraduate biology curriculum is lagging behind, in part due to a lack of instructors willing and able to teach basic bioinformatics in classes that don't specifically focus on quantitative skill development, such as statistics or computer sciences. To help undergraduate course instructors who themselves did not learn bioinformatics as part of their own education and are hesitant to plunge into teaching big data analysis, a module was developed that is written in plain-enough language, using publicly available computing tools and data, to allow novice instructors to teach next-generation sequence analysis to upper-level undergraduate students...
January 2018: PLoS Computational Biology
https://www.readbyqxmd.com/read/29297370/reverse-engineering-of-gene-networks-for-regulating-early-blood-development-from-single-cell-measurements
#7
Jiangyong Wei, Xiaohua Hu, Xiufen Zou, Tianhai Tian
BACKGROUND: Recent advances in omics technologies have raised great opportunities to study large-scale regulatory networks inside the cell. In addition, single-cell experiments have measured the gene and protein activities in a large number of cells under the same experimental conditions. However, a significant challenge in computational biology and bioinformatics is how to derive quantitative information from the single-cell observations and how to develop sophisticated mathematical models to describe the dynamic properties of regulatory networks using the derived quantitative information...
December 28, 2017: BMC Medical Genomics
https://www.readbyqxmd.com/read/29297287/scaling-bioinformatics-applications-on-hpc
#8
Mike Mikailov, Fu-Jyh Luo, Stuart Barkley, Lohit Valleru, Stephen Whitney, Zhichao Liu, Shraddha Thakkar, Weida Tong, Nicholas Petrick
BACKGROUND: Recent breakthroughs in molecular biology and next generation sequencing technologies have led to the expenential growh of the sequence databases. Researchrs use BLAST for processing these sequences. However traditional software parallelization techniques (threads, message passing interface) applied in newer versios of BLAST are not adequate for processing these sequences in timely manner. METHODS: A new method for array job parallelization has been developed which offers O(T) theoretical speed-up in comparison to multi-threading and MPI techniques...
December 28, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29297277/proceedings-of-the-2017-midsouth-computational-biology-and-bioinformatics-society-mcbios-conference
#9
Jonathan D Wren, Mikhail G Dozmorov, Inimary Toby, Bindu Nanduri, Ramin Homayouni, Prashanti Manda, Shraddha Thakkar
No abstract text is available yet for this article.
December 28, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29277877/comparative-genomics-in-drosophila
#10
Martin Oti, Attilio Pane, Michael Sammeth
Since the pioneering studies of Thomas Hunt Morgan and coworkers at the dawn of the twentieth century, Drosophila melanogaster and its sister species have tremendously contributed to unveil the rules underlying animal genetics, development, behavior, evolution, and human disease. Recent advances in DNA sequencing technologies launched Drosophila into the post-genomic era and paved the way for unprecedented comparative genomics investigations. The complete sequencing and systematic comparison of the genomes from 12 Drosophila species represents a milestone achievement in modern biology, which allowed a plethora of different studies ranging from the annotation of known and novel genomic features to the evolution of chromosomes and, ultimately, of entire genomes...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29240760/novel-linear-motif-filtering-protocol-reveals-the-role-of-the-lc8-dynein-light-chain-in-the-hippo-pathway
#11
Gábor Erdős, Tamás Szaniszló, Mátyás Pajkos, Borbála Hajdu-Soltész, Bence Kiss, Gábor Pál, László Nyitray, Zsuzsanna Dosztányi
Protein-protein interactions (PPIs) formed between short linear motifs and globular domains play important roles in many regulatory and signaling processes but are highly underrepresented in current protein-protein interaction databases. These types of interactions are usually characterized by a specific binding motif that captures the key amino acids shared among the interaction partners. However, the computational proteome-level identification of interaction partners based on the known motif is hindered by the huge number of randomly occurring matches from which biologically relevant motif hits need to be extracted...
December 14, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/29236971/new-algorithms-to-represent-complex-pseudoknotted-rna-structures-in-dot-bracket-notation
#12
Maciej Antczak, Mariusz Popenda, Tomasz Zok, Michal Zurkowski, Ryszard W Adamiak, Marta Szachniuk
Motivation: Understanding the formation, architecture, and roles of pseudoknots in RNA structures are one of the most difficult challenges in RNA computational biology and structural bioinformatics. Methods predicting pseudoknots typically perform this with poor accuracy, often despite experimental data incorporation. Existing bioinformatic approaches differ in terms of pseudoknots' recognition and revealing their nature. A few ways of pseudoknot classification exist, most common ones refer to a genus or order...
December 11, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29236675/selected-extended-papers-of-the-11th-international-conference-on-practical-applications-of-computational-biology-and-bioinformatics-pacbb
#13
EDITORIAL
Florentino Fdez-Riverola, Miguel Rocha
No abstract text is available yet for this article.
December 13, 2017: Journal of Integrative Bioinformatics
https://www.readbyqxmd.com/read/29234465/ten-quick-tips-for-machine-learning-in-computational-biology
#14
REVIEW
Davide Chicco
Machine learning has become a pivotal tool for many projects in computational biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical researchers often do not have enough experience to run a data mining project effectively, and therefore can follow incorrect practices, that may lead to common mistakes or over-optimistic results. With this review, we present ten quick tips to take advantage of machine learning in any computational biology context, by avoiding some common errors that we observed hundreds of times in multiple bioinformatics projects...
2017: BioData Mining
https://www.readbyqxmd.com/read/29230204/a-comprehensive-overview-of-online-resources-to-identify-and-predict-bacterial-essential-genes
#15
REVIEW
Chong Peng, Yan Lin, Hao Luo, Feng Gao
Genes critical for the survival or reproduction of an organism in certain circumstances are classified as essential genes. Essential genes play a significant role in deciphering the survival mechanism of life. They may be greatly applied to pharmaceutics and synthetic biology. The continuous progress of experimental method for essential gene identification has accelerated the accumulation of gene essentiality data which facilitates the study of essential genes in silico. In this article, we present some available online resources related to gene essentiality, including bioinformatic software tools for transposon sequencing (Tn-seq) analysis, essential gene databases and online services to predict bacterial essential genes...
2017: Frontiers in Microbiology
https://www.readbyqxmd.com/read/29228285/matrix-factorization-based-data-fusion-for-the-prediction-of-lncrna-disease-associations
#16
Guangyuan Fu, Jun Wang, Carlotta Domeniconi, Guoxian Yu
Motivation: Long non-coding RNAs (lncRNAs) play crucial roles in complex disease diagnosis, prognosis, prevention, and treatment, but only a small portion of lncRNA-disease associations have been experimentally verified. Various computational models have been proposed to identify lncRNA-disease associations by integrating heterogeneous data sources. However, existing models generally ignore the intrinsic structure of data sources or treat them as equally relevant, while they may not be...
December 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228271/litpathexplorer-a-confidence-based-visual-text-analytics-tool-for-exploring-literature-enriched-pathway-models
#17
Axel J Soto, Chrysoula Zerva, Riza Batista-Navarro, Sophia Ananiadou
Motivation: Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. Results: We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i...
December 8, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29228186/aether-leveraging-linear-programming-for-optimal-cloud-computing-in-genomics
#18
Jacob M Luber, Braden T Tierney, Evan M Cofer, Chirag J Patel, Aleksandar D Kostic
Motivation: Across biology we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Results: Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective, and scalable framework that uses linear programming (LP) to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis and provides an easy transition from users' existing HPC pipelines...
December 8, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29219084/an-improved-bayesian-network-method-for-reconstructing-gene-regulatory-network-based-on-candidate-auto-selection
#19
Linlin Xing, Maozu Guo, Xiaoyan Liu, Chunyu Wang, Lei Wang, Yin Zhang
BACKGROUND: The reconstruction of gene regulatory network (GRN) from gene expression data can discover regulatory relationships among genes and gain deep insights into the complicated regulation mechanism of life. However, it is still a great challenge in systems biology and bioinformatics. During the past years, numerous computational approaches have been developed for this goal, and Bayesian network (BN) methods draw most of attention among these methods because of its inherent probability characteristics...
November 17, 2017: BMC Genomics
https://www.readbyqxmd.com/read/29216773/foreword-special-issue-on-selected-papers-from-the-9th-international-conference-on-bioinformatics-and-computational-biology-bicob-2017
#20
Oliver Eulenstein, Qin Ding, Hisham Al-Mubaid
No abstract text is available yet for this article.
December 7, 2017: Journal of Bioinformatics and Computational Biology
keyword
keyword
45746
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"