A Detailed Catalogue of Multi-Omics Methodologies for Identification Of
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Use of Omics Data in Fracture Prediction; a Scoping and Systematic Review in Horses and Humans
animals Review Use of Omics Data in Fracture Prediction; a Scoping and Systematic Review in Horses and Humans Seungmee Lee 1,*, Melissa E. Baker 1, Michael Clinton 2 and Sarah E. Taylor 1 1 The Dick Vet Equine Hospital, The Roslin Institute, Easter Bush, Roslin, Midlothian EH25 9RG, UK; [email protected] (M.E.B.); [email protected] (S.E.T.) 2 The RICE Group, Division of Gene Function and Development, The Roslin Institute, Easter Bush, Roslin, Midlothian EH25 9RG, UK; [email protected] * Correspondence: [email protected] Simple Summary: Despite many recent advances in imaging and epidemiological data analysis, musculoskeletal injuries continue to be a welfare issue in racehorses. Omics studies describe the study of protein, genetic material (both DNA and RNA, including microRNAs—small non-coding ribonucleic acids) and metabolites that may provide insights into the pathophysiology of disease or opportunities to monitor response to treatment when measured in bodily fluids. As these fields of study are scientifically complex and highly specialised, it is timely to perform a review of the current literature to allow for the design of robust studies that allow for repeatable work. Systematic reviews have been introduced into the medical literature and are a methodological way of searching for relevant papers followed by critical review of the content and a detection of biases. The objectives of the current systematic review were to identify and critically appraise the literature pertaining to microRNA (miRNA) and their target genes that are correlated with stress fractures in racehorses and humans. -
A Comprehensive Analysis of the Usability and Archival Stability of Omics Computational
bioRxiv preprint doi: https://doi.org/10.1101/452532; this version posted October 25, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Title: A comprehensive analysis of the usability and archival stability of omics computational tools and resources 1,2$# 2$ 1 1 3 1 Serghei Mangul , Thiago Mosqueiro , Dat Duong , Keith Mitchell ,Varuni Sarwal , Brian Hill , 4 1 1 1 7 Jaqueline Brito , Russell Jared Littman , Benjamin Statz , Angela Ka-Mei Lam , Gargi Dayama , 7 2 5 1,6 7,8 Laura Grieneisen , Lana S. Martin , Jonathan Flint , Eleazar Eskin , Ran Blekhman 1 Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA 2 Institute for Quantitative and Computational Biosciences, University of California Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA 90095, USA 3 Indian Institute of Technology Delhi, Hauz Khas, New Delhi, Delhi 110016, India 4 Institute of Mathematics and Computer Science, University of São Paulo, São Paulo, Brazil 5 Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90095, USA 6 Department of Human Genetics, University of California Los Angeles, 695 Charles E. Young Drive South, Los Angeles, CA 90095, USA 7 Department of Genetics, Cell Biology and Development, University of Minnesota, 321 Church St SE, Minneapolis, MN 55455, USA 8 Department of Ecology, Evolution, and Behavior, University of Minnesota, 100 Ecology Building, 1987 Upper Buford Cir, Falcon Heights, MN 55108, USA $ - These authors contributed equally to the paper # - Corresponding author 1 bioRxiv preprint doi: https://doi.org/10.1101/452532; this version posted October 25, 2018. -
The 'Omics Revolution: How an Obsession with Compiling Lists Is
The ‘omics revolution: how an obsession with compiling lists is threatening the ancient art of experimental design. Claudio D Stern Department of Cell & Developmental Biology, University College London, Gower Street, London WC1E 6BT, UK. [email protected] The last quarter of a century ushered in a transformation in Biology following the huge successes in sequencing entire genomes of organisms (including humans) with increasing precision and speed and rapidly decreasing cost: genomics. Later other “omics” approaches followed: proteomics, metabolomics, epigenomics, and many more. Huge quantities of data were generated and new computational methods to find hidden correlations emerged. Almost imperceptibly, however, it seems that this has led to a crisis in our ability to design elegant experiments to establish causality. Imagine an extra-terrestrial excursion to planet Earth to discover about life on this planet. A spaceship with alien scientists lands in a park with many statues on display, representing important people from British history. The aliens unload their sophisticated analytical equipment and start to investigate. The first one uses a mass spectrometer – s/he approaches each statue and analyse it: one statue contains 5% copper, 10% iron, 17% aluminium, 63% lead. Another statue seems to consist mainly of carbon and a little water. A third object is made of granite. And so on. Another scientist follows: their analysis with a powerful super-resolution electron microscope reveals different sets of atomic structures. A third scientist uses a balance and lists the mass of each statue. A fourth measures the dimensions – some statues are very small, others quite large, and they have different overall shapes: some are tall, some are rather rounded. -
From Proteomics to Systems Biology Outline and Learning Objectives
From Proteomics to Systems Biology Outline and learning objectives “Omics” science provides global analysis tools to study entire systems • How to obtain omics - data • What can we learn? Limitations? • Integration of omics - data • In-class practice: Omics-data visualization Integration of “omics”- information Omics - data provide systems-level information Omics - data provide systems-level information Whole-genome sequencing Microarrays 2D-electrophoresis, mass spectrometry Joyce & Palsson, 2006 Joyce & Palsson, 2006 Transcriptomics (indirectly) tells about Proteomics aims to detect and quantify RNA-transcript abundances a system’s entire protein content ! primary genomic readout Strengths: - very good genome-wide coverage - variety of commercial products Drawback: No protein-level info!! -> RNA degradation Strengths: -> Post-translational modifications -> info about post-translational modifications => validation by e.g. RT-PCR -> high throughput possible due to increasing quality and cycle speed of mass spec instrumentation Limitations: - coverage dependent on sample, preparation & separation method - bias towards most highly abundant proteins Omics - data provide systems-level information Metabolomics and Lipidomics Detector Metabolites GC-MS extracted NMR from cell lysate Glycan arrays, Lipids Glyco-gene chips, mass spec / NMR of carbohydrates ESI-MS/MS Joyce & Palsson, 2006 Metabolomics and Lipidomics Metabolomics and Lipidomics Metabolomics: Metabolomics: Large-scale measurement of cellular metabolites Large-scale measurement of -
Impacts of Genomics and Other 'Omics' for the Crop, Forestry, Livestock
Impacts of genomics and other ‘omics’ for the crop, forestry, livestock, fishery and agro-industry sectors in developing countries 1. Introduction Advances in genomics, the study of all the genetic material (i.e. the genome) of an organism, have been remarkable in recent years. Publication of the first draft of the human genome in 2001 was a milestone, quickly followed by that of the first crop (rice) in 2002 and the first farm animal (chicken) in 2004. Huge technological advancements have meant that sequencing has become dramatically quicker and cheaper over time, so the genomes of many of the important crops, livestock, forest trees, aquatic animals and agricultural pests are now already sequenced or soon will be. The FAO Biotechnology Forum (http://www.fao.org/biotech/biotech-forum/) is hosting this e-mail conference to look at the impacts that genomics, and the other related 'omics', have had so far on food and agriculture in developing countries as well as their potential impacts in the near future. Before looking at genomics in more detail, a quick overview of some basic genetic concepts can be provided [for more technical details, see FAO (2011a) or the FAO biotechnology glossary (FAO, 2001)]. All living things are made up of cells that contain genetic material called DNA, a molecule made up of a long chain of nitrogen-containing bases (of four kinds: A, C, G and T). DNA is organized as a double helix, where two DNA chains are held together through bonding of the bases, where A bonds with T and C bonds with G. -
New Technologies and Their Impact on 'Omics' Research
Available online at www.sciencedirect.com New technologies and their impact on ‘omics’ research Editorial overview Matthew Bogyo and Pauline M Rudd Current Opinion in Chemical Biology 2013, 17:1–3 For a complete overview see the Issue 1367-5931/$ – see front matter, Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.cbpa.2013.01.005 Matthew Bogyo The use of the suffix ‘ome’ is defined in the Oxford English dictionary as ‘being used in cellular and molecular biology to form nouns with the sense Department of Pathology, Stanford University ‘‘all constituents considered collectively’’’. Interestingly, the use of the School of Medicine, Stanford, CA, USA e-mail: [email protected] ‘ome’ suffix in biology dates back to the early 1900s when it was first used to describe a ‘biome’ and genome (although originally in German as genom). Matthew Bogyo received his BSc degree in Over the past few decades, the use of the omics suffix has rapidly increased, Chemistry from Bates College in 1993 and a due in a large part, to the rapid growth in technologies that allow global PhD in Biochemistry from the Massachusetts analysis of samples on a systems level. The familiarity of the ‘omics’ term Institute of Technology in 1997. He became a also was rapidly advanced by the completion of the human genome in the Faculty Fellow at the University of California, early 2000s. Since that time, we have seen the term ‘omics’ move beyond use San Francisco in 1998. In 2001, he moved to for genomics and proteomics and gain acceptance for a diverse array of Celera Genomics to head the Department of Chemical Proteomics until 2003 when he systems biology applications. -
Multi-Omics: an Opportunity to Dive Into Systems Biology
Brazilian Journal of Analytical Chemistry 2020, Volume 7, Issue 29, pp 18-44 doi: 10.30744/brjac.2179-3425.RV-03-2020 REVIEW Multi-omics: An Opportunity to Dive into Systems Biology Emerson Andrade Ferreira dos Santos1 Elisa Castañeda Santa Cruz1 Henrique Caracho Ribeiro1 Luidy Darllan Barbosa1 Flávia da Silva Zandonadi1 Alessandra Sussulini1,2,* 1Laboratory of Bioanalytics and Integrated Omics (LaBIOmics), Department of Analytical Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), P.O. Box 6154, 13083-970, Campinas, SP, Brazil 2National Institute of Science and Technology for Bioanalytics – INCTBio, Institute of Chemistry, University of Campinas (UNICAMP), P.O. Box 6154, 13083-970, Campinas, SP, Brazil Omics data integration employing multi-omics approach is an outstanding opportunity to design a reliable picture of the biochemistry and dynamics of biological systems, as well as prioritize strategies for biomarker discovery. Biological functions are characterized by complex interaction networks, in which the dynamics of biomolecules manages physical and biochemical processes. However, since the emergence of omic sciences, researchers are still looking for the most accurate method to classify and determine the identity and function of biomarkers that describe a system and the ongoing biological processes. Thus, according to the strategies unveiled in the multi-omics literature, this is considered a challenging science field. Therefore, this review describes a workflow example regarding multi-omics data integration, indicating mathematical and computational tools in analysis pipelines that use various methods to perform a sequence of tasks, which would be able to describe biological processes within the systems biology context. Keywords: multi-omics, data integration tools, omics INTRODUCTION The application of computational and mathematical modeling towards a deeper and broader understanding of biological systems is called systems biology. -
MOBN: an Interactive Database of Multi-Omics Biological Networks Cheng Zhang1,#,*, Muhammad Arif1,#, Xiangyu Li1, Sunjae Lee1, Abdellah Tebani1, Wenyu Zhou2, Brian D
bioRxiv preprint doi: https://doi.org/10.1101/662502; this version posted June 8, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. MOBN: an interactive database of multi-omics biological networks Cheng Zhang1,#,*, Muhammad Arif1,#, Xiangyu Li1, Sunjae Lee1, Abdellah Tebani1, Wenyu Zhou2, Brian D. Piening3, Linn Fagerberg1, Nathan Price4, Leroy Hood4, Michael P. Snyder2, Jens Nielsen5, Mathias Uhlen1, Adil Mardinoglu1,6,* 1Science for Life Laboratory, KTH – Royal Institute of Technology, Stockholm, SE-171 21, Sweden 2Department of Genetics, Stanford University, Stanford, CA 94305, USA 3Earle A Chiles Research Institute and Providence Cancer Institute, Portland, OR 97213, USA 4Institute of Systems Biology, Seattle, USA 5Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden 6Centre for Host–Microbiome Interactions, Dental Institute, King's College London, London, SE1 9RT, United Kingdom #These authors contributed equally. *To whom correspondence should be addressed. Abstract Summary: The associations among different omics are essential to understand human wellness and disease. However, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present an interactive database of multi-omics biological networks (MOBN) and describe associations between clinical chemistry, anthropometrics, plasma proteome, plasma metabolome and gut microbiome obtained from the same individuals. MOBN allows the user to interactively explore the association of a single feature with other omics data and customize its specific context (e.g. -
SCIENCE CITATION INDEX EXPANDED - JOURNAL LIST Total Journals: 8631
SCIENCE CITATION INDEX EXPANDED - JOURNAL LIST Total journals: 8631 1. 4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH 2. AAPG BULLETIN 3. AAPS JOURNAL 4. AAPS PHARMSCITECH 5. AATCC REVIEW 6. ABDOMINAL IMAGING 7. ABHANDLUNGEN AUS DEM MATHEMATISCHEN SEMINAR DER UNIVERSITAT HAMBURG 8. ABSTRACT AND APPLIED ANALYSIS 9. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 10. ACADEMIC EMERGENCY MEDICINE 11. ACADEMIC MEDICINE 12. ACADEMIC PEDIATRICS 13. ACADEMIC RADIOLOGY 14. ACCOUNTABILITY IN RESEARCH-POLICIES AND QUALITY ASSURANCE 15. ACCOUNTS OF CHEMICAL RESEARCH 16. ACCREDITATION AND QUALITY ASSURANCE 17. ACI MATERIALS JOURNAL 18. ACI STRUCTURAL JOURNAL 19. ACM COMPUTING SURVEYS 20. ACM JOURNAL ON EMERGING TECHNOLOGIES IN COMPUTING SYSTEMS 21. ACM SIGCOMM COMPUTER COMMUNICATION REVIEW 22. ACM SIGPLAN NOTICES 23. ACM TRANSACTIONS ON ALGORITHMS 24. ACM TRANSACTIONS ON APPLIED PERCEPTION 25. ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION 26. ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS 27. ACM TRANSACTIONS ON COMPUTATIONAL LOGIC 28. ACM TRANSACTIONS ON COMPUTER SYSTEMS 29. ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION 30. ACM TRANSACTIONS ON DATABASE SYSTEMS 31. ACM TRANSACTIONS ON DESIGN AUTOMATION OF ELECTRONIC SYSTEMS 32. ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS 33. ACM TRANSACTIONS ON GRAPHICS 34. ACM TRANSACTIONS ON INFORMATION AND SYSTEM SECURITY 35. ACM TRANSACTIONS ON INFORMATION SYSTEMS 36. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 37. ACM TRANSACTIONS ON INTERNET TECHNOLOGY 38. ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA 39. ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE 40. ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION 41. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 42. ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS 43. ACM TRANSACTIONS ON RECONFIGURABLE TECHNOLOGY AND SYSTEMS 44. -
Multi-Omics Approaches and Radiation on Lipid Metabolism in Toothed Whales
life Review Multi-Omics Approaches and Radiation on Lipid Metabolism in Toothed Whales Jayan D. M. Senevirathna 1,2,* and Shuichi Asakawa 1 1 Laboratory of Aquatic Molecular Biology and Biotechnology, Department of Aquatic Bioscience, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan; [email protected] 2 Department of Animal Science, Faculty of Animal Science and Export Agriculture, Uva Wellassa University, Badulla 90000, Sri Lanka * Correspondence: [email protected] Abstract: Lipid synthesis pathways of toothed whales have evolved since their movement from the terrestrial to marine environment. The synthesis and function of these endogenous lipids and affecting factors are still little understood. In this review, we focused on different omics approaches and techniques to investigate lipid metabolism and radiation impacts on lipids in toothed whales. The selected literature was screened, and capacities, possibilities, and future approaches for identify- ing unusual lipid synthesis pathways by omics were evaluated. Omics approaches were categorized into the four major disciplines: lipidomics, transcriptomics, genomics, and proteomics. Genomics and transcriptomics can together identify genes related to unique lipid synthesis. As lipids interact with proteins in the animal body, lipidomics, and proteomics can correlate by creating lipid-binding proteome maps to elucidate metabolism pathways. In lipidomics studies, recent mass spectroscopic methods can address lipid profiles; however, the determination of structures of lipids are challeng- ing. As an environmental stress, the acoustic radiation has a significant effect on the alteration of Citation: Senevirathna, J.D.M.; Asakawa, S. Multi-Omics Approaches lipid profiles. Radiation studies in different omics approaches revealed the necessity of multi-omics and Radiation on Lipid Metabolism applications. -
From Omics to Systems Biology: Towards a More Complete Description and Understanding of Biology
First Words From omics to systems biology: towards a more complete description and understanding of biology reductionist approaches (for example, focusing on single genes and/or proteins) to generate data that is difficult to accommodate in the context of the biology of the organism being studied. And the reason for this is not that the science is flawed, it’s just that biological systems are complex and reductionist approaches, on Paul Chambers their own, do not deal well with complexity. Research Manager, The Australian Wine Research Institute What is meant by complexity in this context? The components PO Box 197, Glen Osmond SA 5064 of a biological system (for example, genes, proteins, metabolites www.awri.com.au and so on) function in networks and these networks interact [email protected] with each other. For example, a gene might be knocked out with little or no impact on a phenotype that, in other experiments, it has been shown to affect. This might be because other genes “If you try and take a cat apart to see how it works, the have compensated; there is often more than one route to a first thing you have on your hands is a non-working cat.” particular phenotype and the same gene can produce a different – Douglas Adams phenotype in different genetic backgrounds. Technology sets limits on what can be achieved in New technologies, the names of which are suffixed –omics research. The advent of genetic engineering accompanied (meaning a totality of some sort), are, however, enabling the by the development of monoclonal antibody technology development of holistic approaches in biological experiments. -
Translating Cancer 'Omics' to Improved Outcomes
Downloaded from genome.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press Perspective Translating cancer ‘omics’ to improved outcomes Emily A. Vucic,1,2,6,7 Kelsie L. Thu,1,6 Keith Robison,3 Leszek A. Rybaczyk,4 Raj Chari,1,2,5 Carlos E. Alvarez,4 and Wan L. Lam1,2 1British Columbia Cancer Research Centre, Vancouver V5Z 1L3, Canada; 2Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver V6T 1Z4, Canada; 3Warp Drive Bio, Cambridge, Massachusetts 02142, USA; 4Center for Molecular and Human Genetics, The Research Institute at Nationwide Children’s Hospital, Columbus, Ohio 43205, USA; 5Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA The genomics era has yielded great advances in the understanding of cancer biology. At the same time, the immense complexity of the cancer genome has been revealed, as well as a striking heterogeneity at the whole-genome (or omics) level that exists between even histologically similar tumors. The vast accrual and public availability of multi-omics da- tabases with associated clinical annotation including tumor histology, patient response, and outcome are a rich resource that has the potential to lead to rapid translation of high-throughput omics to improved overall survival. We focus on the unique advantages of a multidimensional approach to genomic analysis in this new high-throughput omics age and discuss the implications of the changing cancer demographic to translational omics research. The remarkable technological breakthroughs of the last 10 yr have disruptions—is critical for the translation of omics findings (Hudson reshaped how we view the cancer genome; therefore, so must our et al.