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https://www.readbyqxmd.com/read/29352257/robust-phenotype-prediction-from-gene-expression-data-using-differential-shrinkage-of-co-regulated-genes
#1
Kourosh Zarringhalam, David Degras, Christoph Brockel, Daniel Ziemek
Discovery of robust diagnostic or prognostic biomarkers is a key to optimizing therapeutic benefit for select patient cohorts - an idea commonly referred to as precision medicine. Most discovery studies to derive such markers from high-dimensional transcriptomics datasets are weakly powered with sample sizes in the tens of patients. Therefore, highly regularized statistical approaches are essential to making generalizable predictions. At the same time, prior knowledge-driven approaches have been successfully applied to the manual interpretation of high-dimensional transcriptomics datasets...
January 19, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29352030/the-daunting-polygenicity-of-mental-illness-making-a-new-map
#2
REVIEW
Steven E Hyman
An epochal opportunity to elucidate the pathogenic mechanisms of psychiatric disorders has emerged from advances in genomic technology, new computational tools and the growth of international consortia committed to data sharing. The resulting large-scale, unbiased genetic studies have begun to yield new biological insights and with them the hope that a half century of stasis in psychiatric therapeutics will come to an end. Yet a sobering picture is coming into view; it reveals daunting genetic and phenotypic complexity portending enormous challenges for neurobiology...
March 19, 2018: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
https://www.readbyqxmd.com/read/29352006/machine-learning-in-cardiovascular-medicine-are-we-there-yet
#3
REVIEW
Khader Shameer, Kipp W Johnson, Benjamin S Glicksberg, Joel T Dudley, Partho P Sengupta
Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed where to look. These include a family of operations encompassing several terms like machine learning, cognitive learning, deep learning and reinforcement learning-based methods that can be used to integrate and interpret complex biomedical and healthcare data in scenarios where traditional statistical methods may not be able to perform...
January 19, 2018: Heart: Official Journal of the British Cardiac Society
https://www.readbyqxmd.com/read/29351467/from-ionic-to-cellular-variability-in-human-atrial-myocytes-an-integrative-computational-and-experimental-study
#4
Anna Muszkiewicz, Xing Liu, Alfonso Bueno-Orovio, Brodie A J Lawson, Kevin Burrage, Barbara Casadei, Blanca Rodriguez
Variability refers to differences in physiological function between individuals, which may translate into different disease susceptibility and treatment efficacy. Experiments in human cardiomyocytes face wide variability and restricted tissue access; under these conditions computational models are a useful complementary tool. We conducted a computational and experimental investigation in cardiomyocytes isolated from samples of the right atrial appendage of patients undergoing cardiac surgery to evaluate the impact of variability in action potentials (APs) and sub-cellular ionic densities on calcium transient dynamics...
December 22, 2017: American Journal of Physiology. Heart and Circulatory Physiology
https://www.readbyqxmd.com/read/29350398/use-of-computational-functional-genomics-in-drug-discovery-and-repurposing-for-analgesic-indications
#5
Jörn Lötsch, Dario Kringel
The novel research area of functional genomics investigates biochemical, cellular, or physiological properties of gene products with the goal of understanding the relationship between the genome and the phenotype. These developments have made analgesic drug research a data-rich discipline mastered only by making use of parallel developments in computer science, including the establishment of knowledge bases, mining methods for big data, machine-learning, and artificial intelligence, (Table ) which will be exemplarily introduced in the following...
January 19, 2018: Clinical Pharmacology and Therapeutics
https://www.readbyqxmd.com/read/29345757/whole-genome-sequencing-analysis-for-cancer-genomics-and-precision-medicine
#6
REVIEW
Hidewaki Nakagawa, Masashi Fujita
Explosive advances of next-generation sequencer (NGS) and computational analyses have been exploring somatic protein-altered mutations in most cancer types and these coding mutation data are intensively accumulated. However, there is limited information on somatic mutations in non-coding regions including introns, regulatory elements, and non-coding RNAs, structural variants and pathogen in cancer genomes remain widely unexplored. Whole genome sequencing (WGS) approaches can comprehensively explore all types of genomic alterations in cancer and help us to better understand the whole landscape of driver mutations and mutational signature in cancer genomes and elucidate functional or clinical implications of these unexplored genomic regions and mutational signature...
January 18, 2018: Cancer Science
https://www.readbyqxmd.com/read/29344893/profiling-tumor-infiltrating-immune-cells-with-cibersort
#7
Binbin Chen, Michael S Khodadoust, Chih Long Liu, Aaron M Newman, Ash A Alizadeh
Tumor infiltrating leukocytes (TILs) are an integral component of the tumor microenvironment and have been found to correlate with prognosis and response to therapy. Methods to enumerate immune subsets such as immunohistochemistry or flow cytometry suffer from limitations in phenotypic markers and can be challenging to practically implement and standardize. An alternative approach is to acquire aggregative high dimensional data from cellular mixtures and to subsequently infer the cellular components computationally...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29344739/what-we-have-learned-from-the-recent-meta-analyses-on-diagnostic-methods-for-atherosclerotic-plaque-regression
#8
REVIEW
Giuseppe Biondi-Zoccai, Simona Mastrangeli, Enrico Romagnoli, Mariangela Peruzzi, Giacomo Frati, Leonardo Roever, Arturo Giordano
PURPOSE OF REVIEW: Atherosclerosis has major morbidity and mortality implications globally. While it has often been considered an irreversible degenerative process, recent evidence provides compelling proof that atherosclerosis can be reversed. Plaque regression is however difficult to appraise and quantify, with competing diagnostic methods available. Given the potential of evidence synthesis to provide clinical guidance, we aimed to review recent meta-analyses on diagnostic methods for atherosclerotic plaque regression...
January 17, 2018: Current Atherosclerosis Reports
https://www.readbyqxmd.com/read/29343614/suppressor-of-cytokine-signaling-2-socs2-deletion-protects-bone-health-of-mice-with-dss-induced-inflammatory-bowel-disease
#9
Ross Dobie, Vicky E MacRae, Chloe Pass, Elspeth M Milne, S Faisal Ahmed, Colin Farquharson
Individuals with inflammatory bowel disease (IBD) often present with poor bone health. The development of targeted therapies for this bone loss requires a fuller understanding of the underlying cellular mechanisms. Although bone loss in IBD is multifactorial, the altered sensitivity and secretion of growth hormone (GH) and insulin-like growth factor-1 (IGF-1) in IBD is understood to be a critical contributing mechanism. The expression of suppressor of cytokine signaling 2 (SOCS2), a well-established negative regulator of GH signaling, is stimulated by proinflammatory cytokines...
January 17, 2018: Disease Models & Mechanisms
https://www.readbyqxmd.com/read/29342241/ipat-intelligent-prediction-and-association-tool-for-genomic-research
#10
Chunpeng James Chen, Zhiwu Zhang
Summary: The ultimate goal of genomic research is to effectively predict phenotypes from genotypes so that medical management can improve human health and molecular breeding can increase agricultural production. Genomic prediction or selection (GS) plays a complementary role to genome-wide association studies (GWAS), which is the primary method to identify genes underlying phenotypes. Unfortunately, most computing tools cannot perform data analyses for both GWAS and GS. Furthermore, the majority of these tools are executed through a command-line interface (CLI), which requires programming skills...
January 11, 2018: Bioinformatics
https://www.readbyqxmd.com/read/29340838/text-based-phenotypic-profiles-incorporating-biochemical-phenotypes-of-inborn-errors-of-metabolism-improve-phenomics-based-diagnosis
#11
Jessica J Y Lee, Michael M Gottlieb, Jake Lever, Steven J M Jones, Nenad Blau, Clara D M van Karnebeek, Wyeth W Wasserman
Phenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze phenotypes. Such methods have allowed phenotypic data to be widely used in medical applications, from assisting clinical diagnoses to prioritizing genomic diagnoses. To channel the benefits of phenomics into the field of inborn errors of metabolism (IEM), we have recently launched IEMbase, an expert-curated knowledgebase of IEM and their disease-characterizing phenotypes...
January 16, 2018: Journal of Inherited Metabolic Disease
https://www.readbyqxmd.com/read/29340286/cancer-imaging-phenomics-toolkit-quantitative-imaging-analytics-for-precision-diagnostics-and-predictive-modeling-of-clinical-outcome
#12
Christos Davatzikos, Saima Rathore, Spyridon Bakas, Sarthak Pati, Mark Bergman, Ratheesh Kalarot, Patmaa Sridharan, Aimilia Gastounioti, Nariman Jahani, Eric Cohen, Hamed Akbari, Birkan Tunc, Jimit Doshi, Drew Parker, Michael Hsieh, Aristeidis Sotiras, Hongming Li, Yangming Ou, Robert K Doot, Michel Bilello, Yong Fan, Russell T Shinohara, Paul Yushkevich, Ragini Verma, Despina Kontos
The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer...
January 2018: Journal of Medical Imaging
https://www.readbyqxmd.com/read/29340075/extracting-microtentacle-dynamics-of-tumor-cells-in-a-non-adherent-environment
#13
Eleanor C Ory, Desu Chen, Kristi R Chakrabarti, Peipei Zhang, James I Andorko, Christopher M Jewell, Wolfgang Losert, Stuart S Martin
During metastasis, tumor cells dynamically change their cytoskeleton to traverse through a variety of non-adherent microenvironments, including the vasculature or lymphatics. Due to the challenges of imaging drift in non-adhered tumor cells, the dynamic cytoskeletal phenotypes are poorly understood. We present a new approach to analyze the dynamic cytoskeletal phenotypes of non-adhered cells that support microtentacles (McTNs), which are cell surface projections implicated in metastatic reattachment. Combining a recently-developed cell tethering method with a novel image analysis framework allowed McTN attribute extraction...
December 19, 2017: Oncotarget
https://www.readbyqxmd.com/read/29336514/machine-learned-analysis-of-quantitative-sensory-testing-responses-to-noxious-cold-stimulation-in-healthy-subjects
#14
I Weyer-Menkhoff, M C Thrun, J Lötsch
BACKGROUND: Pain in response to noxious cold has a complex molecular background probably involving several types of sensors. A recent observation has been the multimodal distribution of human cold pain thresholds. This study aimed at analysing reproducibility and stability of this observation and further exploration of data patterns supporting a complex background. METHOD: Pain thresholds to noxious cold stimuli (range 32-0 °C, tonic: temperature decrease -1 °C/s, phasic: temperature decrease -8 °C/s) were acquired in 148 healthy volunteers...
January 16, 2018: European Journal of Pain: EJP
https://www.readbyqxmd.com/read/29330523/closed-loop-control-of-zebrafish-behaviour-in-three-dimensions-using-a-robotic-stimulus
#15
Changsu Kim, Tommaso Ruberto, Paul Phamduy, Maurizio Porfiri
Robotics is continuously being integrated in animal behaviour studies to create customizable, controllable, and repeatable stimuli. However, few systems have capitalized on recent breakthroughs in computer vision and real-time control to enable a two-way interaction between the animal and the robot. Here, we present a "closed-loop control" system to investigate the behaviour of zebrafish, a popular animal model in preclinical studies. The system allows for actuating a biologically-inspired 3D-printed replica in a 3D workspace, in response to the behaviour of a zebrafish...
January 12, 2018: Scientific Reports
https://www.readbyqxmd.com/read/29325759/snps-in-the-vicinity-of-p2x7r-rank-rankl-opg-and-wnt-signalling-pathways-and-their-association-with-bone-phenotypes-in-academy-footballers
#16
Ian Varley, David C Hughes, Julie P Greeves, William D Fraser, Craig Sale
CONTEXT: Genotype plays an important role in influencing bone phenotypes, such as bone mineral density, but the role of genotype in determining responses of bone to exercise has yet to be elucidated. OBJECTIVE: To determine whether 10 SNPs associated with genes in the vicinity of P2X7R, RANK/RANKL/OPG and Wnt Signalling Pathways are associated with bone phenotypes in elite academy footballers (Soccer players) and to determine whether these genotypes are associated with training induced changes in bone...
January 8, 2018: Bone
https://www.readbyqxmd.com/read/29325558/systematic-target-function-annotation-of-human-transcription-factors
#17
Yong Fuga Li, Russ B Altman
BACKGROUND: Transcription factors (TFs), the key players in transcriptional regulation, have attracted great experimental attention, yet the functions of most human TFs remain poorly understood. Recent capabilities in genome-wide protein binding profiling have stimulated systematic studies of the hierarchical organization of human gene regulatory network and DNA-binding specificity of TFs, shedding light on combinatorial gene regulation. We show here that these data also enable a systematic annotation of the biological functions and functional diversity of TFs...
January 10, 2018: BMC Biology
https://www.readbyqxmd.com/read/29324850/generalization-of-the-ewens-sampling-formula-to-arbitrary-fitness-landscapes
#18
Pavel Khromov, Constantin D Malliaris, Alexandre V Morozov
In considering evolution of transcribed regions, regulatory sequences, and other genomic loci, we are often faced with a situation in which the number of allelic states greatly exceeds the size of the population. In this limit, the population eventually adopts a steady state characterized by mutation-selection-drift balance. Although new alleles continue to be explored through mutation, the statistics of the population, and in particular the probabilities of seeing specific allelic configurations in samples taken from the population, do not change with time...
2018: PloS One
https://www.readbyqxmd.com/read/29322925/subtype-identification-from-heterogeneous-tcga-datasets-on-a-genomic-scale-by-multi-view-clustering-with-enhanced-consensus
#19
Menglan Cai, Limin Li
BACKGROUND: The Cancer Genome Atlas (TCGA) has collected transcriptome, genome and epigenome information for over 20 cancers from thousands of patients. The availability of these diverse data types makes it necessary to combine these data to capture the heterogeneity of biological processes and phenotypes and further identify homogeneous subtypes for cancers such as breast cancer. Many multi-view clustering approaches are proposed to discover clusters across different data types. The problem is challenging when different data types show poor agreement of clustering structure...
December 21, 2017: BMC Medical Genomics
https://www.readbyqxmd.com/read/29321860/incorporating-variability-in-simulations-of-seasonally-forced-phenology-using-integral-projection-models
#20
Devin W Goodsman, Brian H Aukema, Nate G McDowell, Richard S Middleton, Chonggang Xu
Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual-based models of insect development and demography. Our derivation, which is based on the rate summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual-based phenology models...
January 2018: Ecology and Evolution
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