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Dive into the research topics where Anna Ratner is active.

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Featured researches published by Anna Ratner.


Nucleic Acids Research | 2012

IMG: the integrated microbial genomes database and comparative analysis system

Victor Markowitz; I-Min A. Chen; Krishna Palaniappan; Ken Chu; Ernest Szeto; Yuri Grechkin; Anna Ratner; Biju Jacob; Jinghua Huang; Peter Williams; Marcel Huntemann; Iain Anderson; Konstantinos Mavromatis; Natalia Ivanova; Nikos C. Kyrpides

The Integrated Microbial Genomes (IMG) system serves as a community resource for comparative analysis of publicly available genomes in a comprehensive integrated context. IMG integrates publicly available draft and complete genomes from all three domains of life with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and reviewing the annotations of genes and genomes in a comparative context. IMGs data content and analytical capabilities have been continuously extended through regular updates since its first release in March 2005. IMG is available at http://img.jgi.doe.gov. Companion IMG systems provide support for expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er), teaching courses and training in microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu) and analysis of genomes related to the Human Microbiome Project (IMG/HMP: http://www.hmpdacc-resources.org/img_hmp).


Nucleic Acids Research | 2014

IMG 4 version of the integrated microbial genomes comparative analysis system

Victor Markowitz; I-Min A. Chen; Krishna Palaniappan; Ken Chu; Ernest Szeto; Manoj Pillay; Anna Ratner; Jinghua Huang; Tanja Woyke; Marcel Huntemann; Iain Anderson; Konstantinos Billis; Neha Varghese; Konstantinos Mavromatis; Amrita Pati; Natalia Ivanova; Nikos C. Kyrpides

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).


Nucleic Acids Research | 2010

The integrated microbial genomes system: an expanding comparative analysis resource

Victor Markowitz; I-Min A. Chen; Krishna Palaniappan; Ken Chu; Ernest Szeto; Yuri Grechkin; Anna Ratner; Iain Anderson; Athanasios Lykidis; Konstantinos Mavromatis; Natalia Ivanova; Nikos C. Kyrpides

The integrated microbial genomes (IMG) system serves as a community resource for comparative analysis of publicly available genomes in a comprehensive integrated context. IMG contains both draft and complete microbial genomes integrated with other publicly available genomes from all three domains of life, together with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and reviewing the annotations of genes and genomes in a comparative context. Since its first release in 2005, IMG’s data content and analytical capabilities have been constantly expanded through regular releases. Several companion IMG systems have been set up in order to serve domain specific needs, such as expert review of genome annotations. IMG is available at http://img.jgi.doe.gov.


Nucleic Acids Research | 2012

IMG/M: the integrated metagenome data management and comparative analysis system

Victor Markowitz; I-Min A. Chen; Ken Chu; Ernest Szeto; Krishna Palaniappan; Yuri Grechkin; Anna Ratner; Biju Jacob; Amrita Pati; Marcel Huntemann; Konstantinos Liolios; Ioanna Pagani; Iain Anderson; Konstantinos Mavromatis; Natalia Ivanova; Nikos C. Kyrpides

The integrated microbial genomes and metagenomes (IMG/M) system provides support for comparative analysis of microbial community aggregate genomes (metagenomes) in a comprehensive integrated context. IMG/M integrates metagenome data sets with isolate microbial genomes from the IMG system. IMG/Ms data content and analytical capabilities have been extended through regular updates since its first release in 2007. IMG/M is available at http://img.jgi.doe.gov/m. A companion IMG/M systems provide support for annotation and expert review of unpublished metagenomic data sets (IMG/M ER: http://img.jgi.doe.gov/mer).


Nucleic Acids Research | 2014

IMG/M 4 version of the integrated metagenome comparative analysis system

Victor Markowitz; I-Min A. Chen; Ken Chu; Ernest Szeto; Krishna Palaniappan; Manoj Pillay; Anna Ratner; Jinghua Huang; Ioanna Pagani; Susannah G. Tringe; Marcel Huntemann; Konstantinos Billis; Neha Varghese; Kristin Tennessen; Konstantinos Mavromatis; Amrita Pati; Natalia Ivanova; Nikos C. Kyrpides

IMG/M (http://img.jgi.doe.gov/m) provides support for comparative analysis of microbial community aggregate genomes (metagenomes) in the context of a comprehensive set of reference genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG/M’s data content and analytical tools have expanded continuously since its first version was released in 2007. Since the last report published in the 2012 NAR Database Issue, IMG/M’s database architecture, annotation and data integration pipelines and analysis tools have been extended to copewith the rapid growth in the number and size of metagenome data sets handled by the system. IMG/M data marts provide support for the analysis of publicly available genomes, expert review of metagenome annotations (IMG/M ER: http://img.jgi.doe.gov/mer) and Human Microbiome Project (HMP)-specific metagenome samples (IMG/M HMP: http://img.jgi.doe.gov/imgm_hmp).


Nucleic Acids Research | 2017

IMG/M: integrated genome and metagenome comparative data analysis system

I-Min A. Chen; Victor Markowitz; Ken Chu; Krishna Palaniappan; Ernest Szeto; Manoj Pillay; Anna Ratner; Jinghua Huang; Evan Andersen; Marcel Huntemann; Neha Varghese; Michalis Hadjithomas; Kristin Tennessen; Torben Nielsen; Natalia Ivanova; Nikos C. Kyrpides

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOEs Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGIs genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support for examining and comparing IMG/Ms datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review (ER) companion system (IMG/M ER: https://img.jgi.doe.gov/mer/). Since the last report published in the 2014 NAR Database Issue, IMG/Ms dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.


Mbio | 2015

IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites

Michalis Hadjithomas; I-Min Amy Chen; Ken Chu; Anna Ratner; Krishna Palaniappan; Ernest Szeto; Jinghua Huang; T. B. K. Reddy; Peter Cimermancic; Michael A. Fischbach; Natalia Ivanova; Victor Markowitz; Nikos C. Kyrpides; Amrita Pati

ABSTRACT In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMGs comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABCs focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMPORTANCE IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMGs extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMGs extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.


PLOS ONE | 2012

IMG/M-HMP: A Metagenome Comparative Analysis System for the Human Microbiome Project

Victor Markowitz; I-Min A. Chen; Ken Chu; Ernest Szeto; Krishna Palaniappan; Biju Jacob; Anna Ratner; Konstantinos Liolios; Ioanna Pagani; Marcel Huntemann; Konstantinos Mavromatis; Natalia Ivanova; Nikos C. Kyrpides

The Integrated Microbial Genomes and Metagenomes (IMG/M) resource is a data management system that supports the analysis of sequence data from microbial communities in the integrated context of all publicly available draft and complete genomes from the three domains of life as well as a large number of plasmids and viruses. IMG/M currently contains thousands of genomes and metagenome samples with billions of genes. IMG/M-HMP is an IMG/M data mart serving the US National Institutes of Health (NIH) Human Microbiome Project (HMP), focussed on HMP generated metagenome datasets, and is one of the central resources provided from the HMP Data Analysis and Coordination Center (DACC). IMG/M-HMP is available at http://www.hmpdacc-resources.org/imgm_hmp/.


BMC Genomics | 2016

Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system

I-Min A. Chen; Victor Markowitz; Krishna Palaniappan; Ernest Szeto; Ken Chu; Jinghua Huang; Anna Ratner; Manoj Pillay; Michalis Hadjithomas; Marcel Huntemann; Natalia Mikhailova; Galina Ovchinnikova; Natalia Ivanova; Nikos C. Kyrpides

BackgroundThe exponential growth of genomic data from next generation technologies renders traditional manual expert curation effort unsustainable. Many genomic systems have included community annotation tools to address the problem. Most of these systems adopted a “Wiki-based” approach to take advantage of existing wiki technologies, but encountered obstacles in issues such as usability, authorship recognition, information reliability and incentive for community participation.ResultsHere, we present a different approach, relying on tightly integrated method rather than “Wiki-based” method, to support community annotation and user collaboration in the Integrated Microbial Genomes (IMG) system. The IMG approach allows users to use existing IMG data warehouse and analysis tools to add gene, pathway and biosynthetic cluster annotations, to analyze/reorganize contigs, genes and functions using workspace datasets, and to share private user annotations and workspace datasets with collaborators. We show that the annotation effort using IMG can be part of the research process to overcome the user incentive and authorship recognition problems thus fostering collaboration among domain experts. The usability and reliability issues are addressed by the integration of curated information and analysis tools in IMG, together with DOE Joint Genome Institute (JGI) expert review.ConclusionBy incorporating annotation operations into IMG, we provide an integrated environment for users to perform deeper and extended data analysis and annotation in a single system that can lead to publications and community knowledge sharing as shown in the case studies.


Nucleic Acids Research | 2017

IMG/VR: A database of cultured and uncultured DNA viruses and retroviruses

David Paez-Espino; I.-Min A. Chen; Krishna Palaniappan; Anna Ratner; Ken Chu; Ernest Szeto; Manoj Pillay; Jinghua Huang; Victor Markowitz; Torben Nielsen; Marcel Huntemann; T. B.K. Reddy; Georgios A. Pavlopoulos; Matthew B. Sullivan; Barbara J. Campbell; Feng Chen; Katherine D. McMahon; Steve J. Hallam; Vincent J. Denef; Ricardo Cavicchioli; Sean M. Caffrey; Wolfgang R. Streit; John Webster; Kim M. Handley; Ghasem H. Salekdeh; Nicolas Tsesmetzis; João C. Setubal; Phillip B. Pope; Wen Tso Liu; Adam R. Rivers

Viruses represent the most abundant life forms on the planet. Recent experimental and computational improvements have led to a dramatic increase in the number of viral genome sequences identified primarily from metagenomic samples. As a result of the expanding catalog of metagenomic viral sequences, there exists a need for a comprehensive computational platform integrating all these sequences with associated metadata and analytical tools. Here we present IMG/VR (https://img.jgi.doe.gov/vr/), the largest publicly available database of 3908 isolate reference DNA viruses with 264 413 computationally identified viral contigs from >6000 ecologically diverse metagenomic samples. Approximately half of the viral contigs are grouped into genetically distinct quasi-species clusters. Microbial hosts are predicted for 20 000 viral sequences, revealing nine microbial phyla previously unreported to be infected by viruses. Viral sequences can be queried using a variety of associated metadata, including habitat type and geographic location of the samples, or taxonomic classification according to hallmark viral genes. IMG/VR has a user-friendly interface that allows users to interrogate all integrated data and interact by comparing with external sequences, thus serving as an essential resource in the viral genomics community.

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Ken Chu

Lawrence Berkeley National Laboratory

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Krishna Palaniappan

Lawrence Berkeley National Laboratory

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Ernest Szeto

Lawrence Berkeley National Laboratory

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I-Min A. Chen

Lawrence Berkeley National Laboratory

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Natalia Ivanova

Russian Academy of Sciences

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Jinghua Huang

Lawrence Berkeley National Laboratory

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Amrita Pati

Joint Genome Institute

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