Joined March 2015
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Proud of our @DR_E_A_M Challenge paper dissecting methods to identify disease modules in molecular networks nature.com/articles/s41592-0… Joint work of >400 participants, data providers and organizers... collaborative science at its best, honored to be part!
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Daniel Marbach retweeted
This @DR_E_A_M challenge compares 75 methods for the identification of disease modules from network data. Users will learn about practical guidelines for how to choose a method and about benchmarks for the analysis. nature.com/articles/s41592-0…
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Proud of our @DR_E_A_M Challenge paper dissecting methods to identify disease modules in molecular networks nature.com/articles/s41592-0… Joint work of >400 participants, data providers and organizers... collaborative science at its best, honored to be part!
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nature.com/articles/s41592-0… Lesson #4: First, identify modules in each network individually, without merging them. Methods attempting to reveal integrated modules across networks failed to significantly improve predictions, likely because our networks were not sufficiently related.
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nature.com/articles/s41592-0… Lesson #5: Network modules reveal core disease genes and pathways. While 1000s of genes may show disease association in GWAS, much more specific disease modules comprising only dozens of genes can be identified within networks.
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Daniel Marbach retweeted
Always wanted to explore this x.com/enricoferrero/status/9…

Fantastic @DR_E_A_M preprint describing results of the disease network module identification challenge: biorxiv.org/content/early/20… #bioinformatics #machinelearning
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Daniel Marbach retweeted
Provided unpublished molecular networks by different collaborators were essential success of our @DR_E_A_M challenge on Disease Module Identification. 👏👏👏 x.com/sysbiomed/status/96440…

Choobdar et al. - Disease Module Identification @DR_E_A_M Challenge outcome w. help from us & use of @omnipathdb biorxiv.org/content/early/20…
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Daniel Marbach retweeted
Fantastic @DR_E_A_M preprint describing results of the disease network module identification challenge: biorxiv.org/content/early/20… #bioinformatics #machinelearning
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Daniel Marbach retweeted
Choobdar et al. - Disease Module Identification @DR_E_A_M Challenge outcome w. help from us & use of @omnipathdb biorxiv.org/content/early/20…

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Daniel Marbach retweeted
An interesting outcome of Disease Module Identification DREAM Challenge.  lnkd.in/dzT7Zsj lnkd.in/dyDzUY4

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Daniel Marbach retweeted
When crowd-surfed molecular networks are married with GWAS we can have a high-resolution glimpse into disease biology x.com/danmarbach/status/9641…

Our latest preprint @DR_E_A_M: Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases biorxiv.org/content/early/20…
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Daniel Marbach retweeted
Our #dreamchallenge paper will be soon submitted to @CellCellPress. Awsome internatinal collaboration. #MachineLearning #NetworkScience#Biologicaldata x.com/danmarbach/status/9641…

Our latest preprint @DR_E_A_M: Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases biorxiv.org/content/early/20…
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Daniel Marbach retweeted
The paper of the DREAM Challenge on molecular network modules is on bioarxiv. Proud to be part of the DREAM Team! biorxiv.org/content/early/20…

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Daniel Marbach retweeted
Dream Challenge - Disease Module Identification preprint is out. Proud of our students who contributed to this effort @BeethikaT @karthikalam @karthikraman @ravi_iitm @IBSE_IITM @rbc_dsai_iitm @iitmadras x.com/danmarbach/status/9641…

Our latest preprint @DR_E_A_M: Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases biorxiv.org/content/early/20…
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Glad to be part of the DREAM Consortium for the contribution titled "Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases" biorxiv.org/content/early/20…

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Our latest preprint @DR_E_A_M: Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases biorxiv.org/content/early/20…
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Our paper on GWAS gene/pathway scoring ranks in top 50 #plosmostdownloaded out of 50mio downloads from @PLOS in 2016 journals.plos.org/ploscompbi…
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Harry Huskey, who helped build the first personal computer, has died. He was 101. nyti.ms/2p0ap31