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Article ; Online: Backbone 1H, 13C, and 15N NMR assignments for the Cyanothece 51142 protein cce_0567: a protein associated with nitrogen fixation in the DUF683 family.

Buchko, Garry W / Sofia, Heidi J

2008 Volume 2, Issue 1, Page(s) 25–28

Abstract: Cyanothece 51142 contains a 78-residue protein, cce_0567, that falls into the DUF683 family of proteins associated with nitrogen fixation. Here we report the assignment of most of the main chain and 13C(beta) side chain resonances of the approximately 40 ...

Abstract	Cyanothece 51142 contains a 78-residue protein, cce_0567, that falls into the DUF683 family of proteins associated with nitrogen fixation. Here we report the assignment of most of the main chain and 13C(beta) side chain resonances of the approximately 40 kDa homo-tetramer.
MeSH term(s)	Amino Acid Sequence ; Bacterial Proteins/chemistry ; Carbon Isotopes/chemistry ; Cyanothece/metabolism ; Magnetic Resonance Spectroscopy/methods ; Molecular Sequence Data ; Molecular Weight ; Nitrogen Fixation ; Nitrogen Isotopes/chemistry ; Protons
Chemical Substances	Bacterial Proteins ; Carbon Isotopes ; Nitrogen Isotopes ; Protons
Language	English
Publishing date	2008-06
Publishing country	Netherlands
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2388861-1
ISSN	1874-270X ; 1874-2718
ISSN (online)	1874-270X
ISSN	1874-2718
DOI	10.1007/s12104-007-9075-3
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Article ; Online: iDASH secure genome analysis competition 2018: blockchain genomic data access logging, homomorphic encryption on GWAS, and DNA segment searching.

Kuo, Tsung-Ting / Jiang, Xiaoqian / Tang, Haixu / Wang, XiaoFeng / Bath, Tyler / Bu, Diyue / Wang, Lei / Harmanci, Arif / Zhang, Shaojie / Zhi, Degui / Sofia, Heidi J / Ohno-Machado, Lucila

BMC medical genomics

2020 Volume 13, Issue Suppl 7, Page(s) 98

MeSH term(s)	Blockchain ; DNA/genetics ; Datasets as Topic ; Genome, Human ; Genome-Wide Association Study ; Humans ; Models, Theoretical
Chemical Substances	DNA (9007-49-2)
Language	English
Publishing date	2020-07-21
Publishing country	England
Document type	Editorial ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2411865-5
ISSN	1755-8794 ; 1755-8794
ISSN (online)	1755-8794
ISSN	1755-8794
DOI	10.1186/s12920-020-0715-0
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Article ; Online: FAVOR: functional annotation of variants online resource and annotator for variation across the human genome.

Nucleic acids research

2022 Volume 51, Issue D1, Page(s) D1300–D1311

Abstract: Large biobank-scale whole genome sequencing (WGS) studies are rapidly identifying a multitude of coding and non-coding variants. They provide an unprecedented resource for illuminating the genetic basis of human diseases. Variant functional annotations ... ...

Abstract	Large biobank-scale whole genome sequencing (WGS) studies are rapidly identifying a multitude of coding and non-coding variants. They provide an unprecedented resource for illuminating the genetic basis of human diseases. Variant functional annotations play a critical role in WGS analysis, result interpretation, and prioritization of disease- or trait-associated causal variants. Existing functional annotation databases have limited scope to perform online queries and functionally annotate the genotype data of large biobank-scale WGS studies. We develop the Functional Annotation of Variants Online Resources (FAVOR) to meet these pressing needs. FAVOR provides a comprehensive multi-faceted variant functional annotation online portal that summarizes and visualizes findings of all possible nine billion single nucleotide variants (SNVs) across the genome. It allows for rapid variant-, gene- and region-level queries of variant functional annotations. FAVOR integrates variant functional information from multiple sources to describe the functional characteristics of variants and facilitates prioritizing plausible causal variants influencing human phenotypes. Furthermore, we provide a scalable annotation tool, FAVORannotator, to functionally annotate large-scale WGS studies and efficiently store the genotype and their variant functional annotation data in a single file using the annotated Genomic Data Structure (aGDS) format, making downstream analysis more convenient. FAVOR and FAVORannotator are available at https://favor.genohub.org.
MeSH term(s)	Humans ; Genome, Human ; Software ; Molecular Sequence Annotation ; Genomics ; Genotype ; Genetic Variation
Language	English
Publishing date	2022-11-09
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	186809-3
ISSN	1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
ISSN (online)	1362-4962 ; 1362-4954
ISSN	0301-5610 ; 0305-1048
DOI	10.1093/nar/gkac966
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Article ; Online: BioGraphE: high-performance bionetwork analysis using the Biological Graph Environment.

Chin, George / Chavarria, Daniel G / Nakamura, Grant C / Sofia, Heidi J

BMC bioinformatics

2008 Volume 9 Suppl 6, Page(s) S6

Abstract: Background: Graphs and networks are common analysis representations for biological systems. Many traditional graph algorithms such as k-clique, k-coloring, and subgraph matching have great potential as analysis techniques for newly available data in ... ...

Abstract	Background: Graphs and networks are common analysis representations for biological systems. Many traditional graph algorithms such as k-clique, k-coloring, and subgraph matching have great potential as analysis techniques for newly available data in biology. Yet, as the amount of genomic and bionetwork information rapidly grows, scientists need advanced new computational strategies and tools for dealing with the complexities of the bionetwork analysis and the volume of the data. Results: We introduce a computational framework for graph analysis called the Biological Graph Environment (BioGraphE), which provides a general, scalable integration platform for connecting graph problems in biology to optimized computational solvers and high-performance systems. This framework enables biology researchers and computational scientists to identify and deploy network analysis applications and to easily connect them to efficient and powerful computational software and hardware that are specifically designed and tuned to solve complex graph problems. In our particular application of BioGraphE to support network analysis in genome biology, we investigate the use of a Boolean satisfiability solver known as Survey Propagation as a core computational solver executing on standard high-performance parallel systems, as well as multi-threaded architectures. Conclusion: In our application of BioGraphE to conduct bionetwork analysis of homology networks, we found that BioGraphE and a custom, parallel implementation of the Survey Propagation SAT solver were capable of solving very large bionetwork problems at high rates of execution on different high-performance computing platforms.
MeSH term(s)	Algorithms ; Computer Graphics ; Computer Simulation ; Models, Biological ; Proteome/metabolism ; Signal Transduction/physiology ; Software
Chemical Substances	Proteome
Language	English
Publishing date	2008-05-28
Publishing country	England
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/1471-2105-9-S6-S6
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Article ; Online: BioGraphE

Sofia Heidi J / Nakamura Grant C / Chavarria Daniel G / Chin George

BMC Bioinformatics, Vol 9, Iss Suppl 6, p S

high-performance bionetwork analysis using the Biological Graph Environment

2008 Volume 6

Abstract: Abstract Background Graphs and networks are common analysis representations for biological systems. Many traditional graph algorithms such as k-clique, k-coloring, and subgraph matching have great potential as analysis techniques for newly available data ...

Abstract	Abstract Background Graphs and networks are common analysis representations for biological systems. Many traditional graph algorithms such as k-clique, k-coloring, and subgraph matching have great potential as analysis techniques for newly available data in biology. Yet, as the amount of genomic and bionetwork information rapidly grows, scientists need advanced new computational strategies and tools for dealing with the complexities of the bionetwork analysis and the volume of the data. Results We introduce a computational framework for graph analysis called the Biological Graph Environment (BioGraphE), which provides a general, scalable integration platform for connecting graph problems in biology to optimized computational solvers and high-performance systems. This framework enables biology researchers and computational scientists to identify and deploy network analysis applications and to easily connect them to efficient and powerful computational software and hardware that are specifically designed and tuned to solve complex graph problems. In our particular application of BioGraphE to support network analysis in genome biology, we investigate the use of a Boolean satisfiability solver known as Survey Propagation as a core computational solver executing on standard high-performance parallel systems, as well as multi-threaded architectures. Conclusion In our application of BioGraphE to conduct bionetwork analysis of homology networks, we found that BioGraphE and a custom, parallel implementation of the Survey Propagation SAT solver were capable of solving very large bionetwork problems at high rates of execution on different high-performance computing platforms.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
Subject code	004
Language	English
Publishing date	2008-05-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
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Article: The third pillar of bacterial signal transduction: classification of the extracytoplasmic function (ECF) σ factor protein family

Staroń, Anna / Sofia, Heidi J / Dietrich, Sascha / Ulrich, Luke E / Liesegang, Heiko / Mascher, Thorsten

Molecular microbiology. 2009 Nov., v. 74, no. 3

2009

Abstract: The ability of a bacterial cell to monitor and adaptively respond to its environment is crucial for survival. After one- and two-component systems, extracytoplasmic function (ECF) σ factors - the largest group of alternative σ factors - represent the ... ...

Abstract	The ability of a bacterial cell to monitor and adaptively respond to its environment is crucial for survival. After one- and two-component systems, extracytoplasmic function (ECF) σ factors - the largest group of alternative σ factors - represent the third fundamental mechanism of bacterial signal transduction, with about six such regulators on average per bacterial genome. Together with their cognate anti-σ factors, they represent a highly modular design that primarily facilitates transmembrane signal transduction. A comprehensive analysis of the ECF σ factor protein family identified more than 40 distinct major groups of ECF σ factors. The functional relevance of this classification is supported by the sequence similarity and domain architecture of cognate anti-σ factors, genomic context conservation, and potential target promoter motifs. Moreover, this phylogenetic analysis revealed unique features indicating novel mechanisms of ECF-mediated signal transduction. This classification, together with the web tool ECFfinder and the information stored in the Microbial Signal Transduction (MiST) database, provides a comprehensive resource for the analysis of ECF σ factor-dependent gene regulation.
Language	English
Dates of publication	2009-11
Size	p. 557-581.
Publisher	Blackwell Publishing Ltd
Publishing place	Oxford, UK
Document type	Article
ZDB-ID	619315-8
ISSN	1365-2958 ; 0950-382X
ISSN (online)	1365-2958
ISSN	0950-382X
DOI	10.1111/j.1365-2958.2009.06870.x
Database	NAL-Catalogue (AGRICOLA)

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Article: Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines.

Ellrott, Kyle / Bailey, Matthew H / Saksena, Gordon / Covington, Kyle R / Kandoth, Cyriac / Stewart, Chip / Hess, Julian / Ma, Singer / Chiotti, Kami E / McLellan, Michael / Sofia, Heidi J / Hutter, Carolyn / Getz, Gad / Wheeler, David / Ding, Li

Cell systems

2018 Volume 6, Issue 3, Page(s) 271–281.e7

Abstract: The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple ... ...

Abstract	The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects.
MeSH term(s)	Algorithms ; Exome ; Genomics/methods ; High-Throughput Nucleotide Sequencing/methods ; Humans ; Information Dissemination/methods ; Mutation ; Neoplasms/genetics ; Sequence Analysis, DNA/methods ; Software ; Exome Sequencing/methods
Language	English
Publishing date	2018-04-26
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2854138-8
ISSN	2405-4720 ; 2405-4712
ISSN (online)	2405-4720
ISSN	2405-4712
DOI	10.1016/j.cels.2018.03.002
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Article: Phylogeny of the bacterial superfamily of Crp-Fnr transcription regulators: exploiting the metabolic spectrum by controlling alternative gene programs.

Körner, Heinz / Sofia, Heidi J / Zumft, Walter G

FEMS microbiology reviews

2003 Volume 27, Issue 5, Page(s) 559–592

Abstract: The Crp-Fnr regulators, named after the first two identified members, are DNA-binding proteins which predominantly function as positive transcription factors, though roles of repressors are also important. Among over 1200 proteins with an N-terminally ... ...

Abstract	The Crp-Fnr regulators, named after the first two identified members, are DNA-binding proteins which predominantly function as positive transcription factors, though roles of repressors are also important. Among over 1200 proteins with an N-terminally located nucleotide-binding domain similar to the cyclic adenosine monophosphate (cAMP) receptor protein, the distinctive additional trait of the Crp-Fnr superfamily is a C-terminally located helix-turn-helix motif for DNA binding. From a curated database of 369 family members exhibiting both features, we provide a protein tree of Crp-Fnr proteins according to their phylogenetic relationships. This results in the assembly of the regulators ArcR, CooA, CprK, Crp, Dnr, FixK, Flp, Fnr, FnrN, MalR, NnrR, NtcA, PrfA, and YeiL and their homologs in distinct clusters. Lead members and representatives of these groups are described, placing emphasis on the less well-known regulators and target processes. Several more groups consist of sequence-derived proteins of unknown physiological roles; some of them are tight clusters of highly similar members. The Crp-Fnr regulators stand out in responding to a broad spectrum of intracellular and exogenous signals such as cAMP, anoxia, the redox state, oxidative and nitrosative stress, nitric oxide, carbon monoxide, 2-oxoglutarate, or temperature. To accomplish their roles, Crp-Fnr members have intrinsic sensory modules allowing the binding of allosteric effector molecules, or have prosthetic groups for the interaction with the signal. The regulatory adaptability and structural flexibility represented in the Crp-Fnr scaffold has led to the evolution of an important group of physiologically versatile transcription factors.
MeSH term(s)	Cyclic AMP Receptor Protein/genetics ; Cyclic AMP Receptor Protein/metabolism ; Escherichia coli Proteins/genetics ; Escherichia coli Proteins/metabolism ; Gene Expression Regulation, Bacterial ; Gram-Negative Bacteria/genetics ; Gram-Negative Bacteria/metabolism ; Gram-Positive Bacteria/genetics ; Gram-Positive Bacteria/metabolism ; Iron-Sulfur Proteins/genetics ; Iron-Sulfur Proteins/metabolism ; Phylogeny ; Transcriptional Activation
Chemical Substances	Cyclic AMP Receptor Protein ; Escherichia coli Proteins ; FNR protein, E coli ; Iron-Sulfur Proteins
Language	English
Publishing date	2003-12
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Review
ZDB-ID	283740-7
ISSN	1574-6976 ; 0168-6445
ISSN (online)	1574-6976
ISSN	0168-6445
DOI	10.1016/S0168-6445(03)00066-4
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Article ; Online: The third pillar of bacterial signal transduction: classification of the extracytoplasmic function (ECF) sigma factor protein family.

Staroń, Anna / Sofia, Heidi J / Dietrich, Sascha / Ulrich, Luke E / Liesegang, Heiko / Mascher, Thorsten

Molecular microbiology

2009 Volume 74, Issue 3, Page(s) 557–581

Abstract: The ability of a bacterial cell to monitor and adaptively respond to its environment is crucial for survival. After one- and two-component systems, extracytoplasmic function (ECF) sigma factors - the largest group of alternative sigma factors - represent ...

Abstract	The ability of a bacterial cell to monitor and adaptively respond to its environment is crucial for survival. After one- and two-component systems, extracytoplasmic function (ECF) sigma factors - the largest group of alternative sigma factors - represent the third fundamental mechanism of bacterial signal transduction, with about six such regulators on average per bacterial genome. Together with their cognate anti-sigma factors, they represent a highly modular design that primarily facilitates transmembrane signal transduction. A comprehensive analysis of the ECF sigma factor protein family identified more than 40 distinct major groups of ECF sigma factors. The functional relevance of this classification is supported by the sequence similarity and domain architecture of cognate anti-sigma factors, genomic context conservation, and potential target promoter motifs. Moreover, this phylogenetic analysis revealed unique features indicating novel mechanisms of ECF-mediated signal transduction. This classification, together with the web tool ECFfinder and the information stored in the Microbial Signal Transduction (MiST) database, provides a comprehensive resource for the analysis of ECF sigma factor-dependent gene regulation.
MeSH term(s)	Amino Acid Motifs/genetics ; Amino Acid Sequence ; Bacteria/genetics ; Bacteria/metabolism ; Bacterial Proteins/classification ; Bacterial Proteins/genetics ; Bacterial Proteins/metabolism ; Gene Expression Profiling ; Gene Expression Regulation, Bacterial ; Genes, Bacterial ; Genome, Bacterial ; Genomics ; Mycobacterium tuberculosis/genetics ; Mycobacterium tuberculosis/metabolism ; Protein Kinases/genetics ; Protein Kinases/metabolism ; Protein Structure, Tertiary/genetics ; RNA, Bacterial/analysis ; RNA, Bacterial/genetics ; Reverse Transcriptase Polymerase Chain Reaction ; Sequence Alignment ; Sigma Factor/classification ; Sigma Factor/genetics ; Sigma Factor/metabolism ; Signal Transduction/genetics ; Virulence Factors/genetics
Chemical Substances	Bacterial Proteins ; RNA, Bacterial ; Sigma Factor ; Virulence Factors ; Protein Kinases (EC 2.7.-)
Language	English
Publishing date	2009-11
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	619315-8
ISSN	1365-2958 ; 0950-382X
ISSN (online)	1365-2958
ISSN	0950-382X
DOI	10.1111/j.1365-2958.2009.06870.x
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Article ; Online: The Human Pangenome Project: a global resource to map genomic diversity.

Wang, Ting / Antonacci-Fulton, Lucinda / Howe, Kerstin / Lawson, Heather A / Lucas, Julian K / Phillippy, Adam M / Popejoy, Alice B / Asri, Mobin / Carson, Caryn / Chaisson, Mark J P / Chang, Xian / Cook-Deegan, Robert / Felsenfeld, Adam L / Fulton, Robert S / Garrison, Erik P / Garrison, Nanibaa' A / Graves-Lindsay, Tina A / Ji, Hanlee / Kenny, Eimear E /

Koenig, Barbara A / Li, Daofeng / Marschall, Tobias / McMichael, Joshua F / Novak, Adam M / Purushotham, Deepak / Schneider, Valerie A / Schultz, Baergen I / Smith, Michael W / Sofia, Heidi J / Weissman, Tsachy / Flicek, Paul / Li, Heng / Miga, Karen H / Paten, Benedict / Jarvis, Erich D / Hall, Ira M / Eichler, Evan E / Haussler, David

Nature

2022 Volume 604, Issue 7906, Page(s) 437–446

Abstract: The human reference genome is the most widely used resource in human genetics and is due for a major update. Its current structure is a linear composite of merged haplotypes from more than 20 people, with a single individual comprising most of the ... ...

Abstract	The human reference genome is the most widely used resource in human genetics and is due for a major update. Its current structure is a linear composite of merged haplotypes from more than 20 people, with a single individual comprising most of the sequence. It contains biases and errors within a framework that does not represent global human genomic variation. A high-quality reference with global representation of common variants, including single-nucleotide variants, structural variants and functional elements, is needed. The Human Pangenome Reference Consortium aims to create a more sophisticated and complete human reference genome with a graph-based, telomere-to-telomere representation of global genomic diversity. Here we leverage innovations in technology, study design and global partnerships with the goal of constructing the highest-possible quality human pangenome reference. Our goal is to improve data representation and streamline analyses to enable routine assembly of complete diploid genomes. With attention to ethical frameworks, the human pangenome reference will contain a more accurate and diverse representation of global genomic variation, improve gene-disease association studies across populations, expand the scope of genomics research to the most repetitive and polymorphic regions of the genome, and serve as the ultimate genetic resource for future biomedical research and precision medicine.
MeSH term(s)	Genome, Human/genetics ; Genomics ; Haplotypes/genetics ; High-Throughput Nucleotide Sequencing ; Humans ; Sequence Analysis, DNA
Language	English
Publishing date	2022-04-20
Publishing country	England
Document type	Journal Article ; Review ; Research Support, N.I.H., Intramural ; Research Support, N.I.H., Extramural
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/s41586-022-04601-8
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