Interactive network visualization in Jupyter notebooks: visJS2jupyter

Rosenthal, Sara Brin; Len, Julia; Webster, Mikayla; Gary, Aaron; Birmingham, Amanda; Fisch, Kathleen

doi:10.1093/bioinformatics/btx581

Cited by 16 publications

(14 citation statements)

References 12 publications

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“…These are plotted using the human homolog nomenclature and the tool visJS2jupyter ( Fig. 1C; Rosenthal et al 2018). Three of the classes include factors that are known to regulate nuclear RNA levels-that is, the exosome, RNA processing and/or export factors, and components of the basic transcription machinery (e.g., TAF3, TAF6, Mediator subunits).…”

Section: Resultsmentioning

confidence: 99%

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Synergistic lethality between BRCA1 and H3K9me2 loss reflects satellite derepression

et al. 2019

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Caenorhabditis elegans has two histone H3 Lys9 methyltransferases, MET-2 (SETDB1 homolog) and SET-25 (G9a/ SUV39H1 related). In worms, we found simple repeat sequences primarily marked by H3K9me2, while transposable elements and silent tissue-specific genes bear H3K9me3. RNA sequencing (RNA-seq) in histone methyltransferase (HMT) mutants shows that MET-2-mediated H3K9me2 is necessary for satellite repeat repression, while SET-25 silences a subset of transposable elements and tissue-specific genes through H3K9me3. A genome-wide synthetic lethality screen showed that RNA processing, nuclear RNA degradation, the BRCA1/BARD1 complex, and factors mediating replication stress survival are necessary for germline viability in worms lacking MET-2 but not SET-25. Unlike set-25 mutants, met-2-null worms accumulated satellite repeat transcripts, which form RNA:DNA hybrids on repetitive sequences, additively with the loss of BRCA1 or BARD1. BRCA1/BARD1-mediated H2A ubiquitination and MET-2 deposited H3K9me2 on satellite repeats are partially interdependent, suggesting both that the loss of silencing generates BRCA-recruiting DNA damage and that BRCA1 recruitment by damage helps silence repeats. The artificial induction of MSAT1 transcripts can itself trigger damage-induced germline lethality in a wild-type background, arguing that the synthetic sterility upon BRCA1/BARD1 and H3K9me2 loss is directly linked to the DNA damage provoked by unscheduled satellite repeat transcription.

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Section: Resultsmentioning

confidence: 99%

“…We include factors in the DNA replication and repair category that were tested secondarily: BRCA1, BARD1, RAD51, ATR. Visualization used visJS2jupyter (Rosenthal et al 2018). (D) Synthetic sterility demonstrated for met-2 set-25 mutants and depletion of the indicated genes by RNAi after one generation at 25°C.…”

Section: Resultsmentioning

confidence: 99%

Synergistic lethality between BRCA1 and H3K9me2 loss reflects satellite derepression

et al. 2019

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“…The identified differentially expressed genes were mapped onto this network to create an AD subnetwork. Network visualization was accomplished using visJS2Jupyter (Rosenthal et al, 2018).…”

Section: Background Interactomementioning

confidence: 99%

Integrating Gene and Protein Expression Reveals Perturbed Functional Networks in Alzheimer’s Disease

et al. 2019

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“…visJS2jupyter is a tool designed to embed interactive networks in Jupyter notebooks to streamline network analysis and to promote reproducible research .…”

Section: Miscellaneous Tools Of Interestmentioning

confidence: 99%

New tools and resources in metabolomics: 2016–2017

Misra¹

2018

Electrophoresis

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Rapid advances in mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based platforms for metabolomics have led to an upsurge of data every single year. Newer high-throughput platforms, hyphenated technologies, miniaturization, and tool kits in data acquisition efforts in metabolomics have led to additional challenges in metabolomics data pre-processing, analysis, interpretation, and integration. Thanks to the informatics, statistics, and computational community, new resources continue to develop for metabolomics researchers. The purpose of this review is to provide a summary of the metabolomics tools, software, and databases that were developed or improved during 2016-2017, thus, enabling readers, developers, and researchers access to a succinct but thorough list of resources for further improvisation, implementation, and application in due course of time.

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Interactive network visualization in Jupyter notebooks: visJS2jupyter

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 16 publications

References 12 publications

Synergistic lethality between BRCA1 and H3K9me2 loss reflects satellite derepression

Synergistic lethality between BRCA1 and H3K9me2 loss reflects satellite derepression

Integrating Gene and Protein Expression Reveals Perturbed Functional Networks in Alzheimer’s Disease

New tools and resources in metabolomics: 2016–2017

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