Data visualization

Image of an anesthetized male Drosophila fruit fly

DRSC/TRiP presentations from June 2020 Boston Area Drosophila Meeting

June 12, 2020
Did you miss the presentations from Claire Hu and Jonathan Zirin at the June 2020 Boston Area Drosophila Meeting? No problem! The slides can be accessed from this post. Click the title above to view the whole post, then scroll down to access the PDFs. These presentations describe what's new and next in bioinformatics and in vivo technologies at the DRSC/TRiP. Feel free to reach out with questions. Interested in the BAD meeting? Info about the meeting can be found here. Read more about DRSC/TRiP presentations from June 2020 Boston Area Drosophila Meeting
Screenshot of the FlyScape tool

Wilinski and colleagues release "FlyScape" for metabolic network visualization

November 7, 2019

The DRSC congratulates Wilinski et al. at the University of Michigan for their release and publication of FlyScape, a tool for metabolic network visualization.

Rapid metabolic shifts occur during the transition between hunger and satiety in Drosophila melanogaster

Daniel Wilinski, Jasmine Winzeler, William Duren, Jenna L. Persons, Kristina J. Holme, Johan Mosquera, Morteza Khabiri, Jason M. Kinchen, Peter L. Freddolino, Alla Karnovsky & Monica Dus 

...

Read more about Wilinski and colleagues release "FlyScape" for metabolic network visualization
Screenshot of online tools

Navigating our online tools -- orthologs, literature mining, qPCR primers, and so much more!

February 14, 2019

We have been taking a critical look at how we organize our online tools on the Online Tools Overview page. And more generally, we have been thinking about new ways to spread the word about the many resources in our suite of online tools. One way that we at the DRSC like to think about these tools is how they fit into the start-to-finish order of events in a screen or other experimental project. Various tools help define lists of genes to be studied, help identify reagents for the study,...

Read more about Navigating our online tools -- orthologs, literature mining, qPCR primers, and so much more!
flySAM

Missed us at ADRC 2018? View our workshop slides!

April 19, 2018
Thank you to all those who attended our workshop at last week's Annual Drosophila Research Conference in Philadelphia, PA, USA. It was great to talk fly stocks, cell screens, and bioinformatics with the community. We are here to help and look forward to continued feedback on the resources we are building to empower your research. PDFs of our workshop presentations are attached to this news item. The slides will help you learn more about our in vivo resources for CRISPR, new pooled cell-based CRISPR screen technology, and bioinformatics resources at our facility.  Feel free to contact... Read more about Missed us at ADRC 2018? View our workshop slides!
Yanhui Hu, Arunachalam Vinayagam, Ankita Nand, Aram Comjean, Verena Chung, Tong Hao, Stephanie E Mohr, and Norbert Perrimon. 11/16/2017. “Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data.” Nucleic Acids Res, 46, D1, Pp. D567-D574.Abstract
Model organism and human databases are rich with information about genetic and physical interactions. These data can be used to interpret and guide the analysis of results from new studies and develop new hypotheses. Here, we report the development of the Molecular Interaction Search Tool (MIST; http://fgrtools.hms.harvard.edu/MIST/). The MIST database integrates biological interaction data from yeast, nematode, fly, zebrafish, frog, rat and mouse model systems, as well as human. For individual or short gene lists, the MIST user interface can be used to identify interacting partners based on protein-protein and genetic interaction (GI) data from the species of interest as well as inferred interactions, known as interologs, and to view a corresponding network. The data, interologs and search tools at MIST are also useful for analyzing 'omics datasets. In addition to describing the integrated database, we also demonstrate how MIST can be used to identify an appropriate cut-off value that balances false positive and negative discovery, and present use-cases for additional types of analysis. Altogether, the MIST database and search tools support visualization and navigation of existing protein and GI data, as well as comparison of new and existing data.
2018 Apr 13

DRSC & TRiP Workshop at ADRC

1:45pm to 3:45pm

Location: 

Philadelphia, PA, USA
The DRSC & TRiP will be hosting a workshop at the Annual Drosophila Research Conference in Philadelphia, PA. The workshop is scheduled for Friday, April 13th from 1:45 to 3:45 PM. Come hear from DRSC & TRiP leaders Norbert Perrimon, Jonathan Zirin (organizer), Claire Yanhui Hu, and Stephanie Mohr. At the workshop, you will learn about new opportunities for community nomination and experiments using CRISPR knockout and activation, as well as learn what's new and popular among our online software and database tools. There will be something for everyone -- we will provide information... Read more about DRSC & TRiP Workshop at ADRC
Yanhui Hu, Aram Comjean, Stephanie E Mohr, The FlyBase Consortium, and Norbert Perrimon. 8/7/2017. “Gene2Function: An Integrated Online Resource for Gene Function Discovery.” G3 (Bethesda).Abstract
One of the most powerful ways to develop hypotheses regarding biological functions of conserved genes in a given species, such as in humans, is to first look at what is known about function in another species. Model organism databases (MODs) and other resources are rich with functional information but difficult to mine. Gene2Function (G2F) addresses a broad need by integrating information about conserved genes in a single online resource.
Arunachalam Vinayagam, Travis E Gibson, Ho-Joon Lee, Bahar Yilmazel, Charles Roesel, Yanhui Hu, Young Kwon, Amitabh Sharma, Yang-Yu Liu, Norbert Perrimon, and Albert-László Barabási. 5/3/2016. “Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets.” Proc Natl Acad Sci U S A, 113, 18, Pp. 4976-81.Abstract

The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets.

Arunachalam Vinayagam, Meghana M Kulkarni, Richelle Sopko, Xiaoyun Sun, Yanhui Hu, Ankita Nand, Christians Villalta, Ahmadali Moghimi, Xuemei Yang, Stephanie E Mohr, Pengyu Hong, John M Asara, and Norbert Perrimon. 9/13/2016. “An Integrative Analysis of the InR/PI3K/Akt Network Identifies the Dynamic Response to Insulin Signaling.” Cell Reports, 16, 11, Pp. 3062-3074.Abstract

Insulin regulates an essential conserved signaling pathway affecting growth, proliferation, and meta- bolism. To expand our understanding of the insulin pathway, we combine biochemical, genetic, and computational approaches to build a comprehensive Drosophila InR/PI3K/Akt network. First, we map the dynamic protein-protein interaction network sur- rounding the insulin core pathway using bait-prey interactions connecting 566 proteins. Combining RNAi screening and phospho-specific antibodies, we find that 47% of interacting proteins affect pathway activity, and, using quantitative phospho- proteomics, we demonstrate that $10% of interact- ing proteins are regulated by insulin stimulation at the level of phosphorylation. Next, we integrate these orthogonal datasets to characterize the structure and dynamics of the insulin network at the level of protein complexes and validate our method by iden- tifying regulatory roles for the Protein Phosphatase 2A (PP2A) and Reptin-Pontin chromatin-remodeling complexes as negative and positive regulators of ribosome biogenesis, respectively. Altogether, our study represents a comprehensive resource for the study of the evolutionary conserved insulin network. 

Ian T Flockhart, Matthew Booker, Yanhui Hu, Benjamin McElvany, Quentin Gilly, Bernard Mathey-Prevot, Norbert Perrimon, and Stephanie E Mohr. 2012. “FlyRNAi.org--the database of the Drosophila RNAi screening center: 2012 update.” Nucleic Acids Res, 40, Database issue, Pp. D715-9.Abstract

FlyRNAi (http://www.flyrnai.org), the database and website of the Drosophila RNAi Screening Center (DRSC) at Harvard Medical School, serves a dual role, tracking both production of reagents for RNA interference (RNAi) screening in Drosophila cells and RNAi screen results. The database and website is used as a platform for community availability of protocols, tools, and other resources useful to researchers planning, conducting, analyzing or interpreting the results of Drosophila RNAi screens. Based on our own experience and user feedback, we have made several changes. Specifically, we have restructured the database to accommodate new types of reagents; added information about new RNAi libraries and other reagents; updated the user interface and website; and added new tools of use to the Drosophila community and others. Overall, the result is a more useful, flexible and comprehensive website and database.

Richelle Sopko, Marianna Foos, Arunachalam Vinayagam, Bo Zhai, Richard Binari, Yanhui Hu, Sakara Randklev, Lizabeth A Perkins, Steven P Gygi, and Norbert Perrimon. 2014. “Combining genetic perturbations and proteomics to examine kinase-phosphatase networks in Drosophila embryos.” Dev Cell, 31, 1, Pp. 114-27.Abstract

Connecting phosphorylation events to kinases and phosphatases is key to understanding the molecular organization and signaling dynamics of networks. We have generated a validated set of transgenic RNA-interference reagents for knockdown and characterization of all protein kinases and phosphatases present during early Drosophila melanogaster development. These genetic tools enable collection of sufficient quantities of embryos depleted of single gene products for proteomics. As a demonstration of an application of the collection, we have used multiplexed isobaric labeling for quantitative proteomics to derive global phosphorylation signatures associated with kinase-depleted embryos to systematically link phosphosites with relevant kinases. We demonstrate how this strategy uncovers kinase consensus motifs and prioritizes phosphoproteins for kinase target validation. We validate this approach by providing auxiliary evidence for Wee kinase-directed regulation of the chromatin regulator Stonewall. Further, we show how correlative phosphorylation at the site level can indicate function, as exemplified by Sterile20-like kinase-dependent regulation of Stat92E.

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