Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome.

Rupam Bhattacharyya, Min Jin Ha, Qingzhi Liu, Rehan Akbani, Han Liang, Veerabhadran Baladandayuthapani

May 2020

Synopsis of Social media discussions

Discussions show strong support and interest through phrases like 'potential use in identifying appropriate preclinical models,' 'Tremendous effort,' and references to real-world applications and research milestones. The tone reflects excitement about the research's implications, with specific mentions of methods, tools, and future uses that indicate deep engagement and belief in its high impact.

A
Agreement
 Moderate agreement

Most discussions express support and enthusiasm for the publication, highlighting its potential impact and usefulness.

I
Interest
 High level of interest

Posts demonstrate high interest, with mentions of tool applications, research insights, and personal academic milestones.

E
Engagement
 High engagement

Users actively reference specific methods like TransPRECISE, connect to wider research goals, and share links to the publication and related tools.

I
Impact
 High level of impact

The discussions suggest the research could significantly influence personalized cancer treatment and preclinical model selection, emphasizing its importance in the field.

Social Mentions

YouTube

2 Videos

Facebook

1 Posts

Twitter

9 Posts

News

1 Articles

Metrics

Video Views

521

Total Likes

36

Extended Reach

191,328

Social Features

13

Timeline: Posts about article

Top Social Media Posts

Posts referencing the article

BayesRx Research Group University of Michigan

May 20, 2020

287 views

TransPRECISE: Advanced Network Modeling for Cancer Precision Medicine

TransPRECISE: Advanced Network Modeling for Cancer Precision Medicine

This presentation introduces TransPRECISE, a Bayesian network framework analyzing cancer patient data and cell lines to identify key pathways and drug targets, aiding personalized cancer treatment. Access the related resources and contact us for feedback.

BayesRx Research Group University of Michigan

August 13, 2020

234 views

  • bioRxiv Published
    @biorxiv_pubd (Twitter)

    Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome published as: https://t.co/6VV817wdO5 #JCO_Clinical_Cancer_Informatics #biorxiv
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    December 26, 2022

  • University of Michigan School of Public Health
    @umichsph (Twitter)

    RT @um_midas: .@veerab and team developed TransPRECISE which has potential use in identifying appropriate preclinical models for prioritizi…
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    May 29, 2020

    1

  • Michigan Institute for Data & AI In Society
    @um_midas (Twitter)

    .@veerab and team developed TransPRECISE which has potential use in identifying appropriate preclinical models for prioritizing specific drug targets across tumor types and in guiding individualized clinical decision making. https://t.co/6WeP2caK5i https://t.co/dDmtJNiWTr
    view full post

    May 29, 2020

    7

    1

  • Tuhin Majumder
    @TuhinMa25031568 (Twitter)

    RT @rupam_mmb: The first paper from my PhD research work (potentially the first chapter of my thesis) is finally online! https://t.co/azeI…
    view full post

    May 24, 2020

    2

  • Journal of Clinical Oncology
    @JCO_ASCO (Twitter)

    Analytic framework has potential use in identifying preclinical models for prioritizing drug targets across tumor types https://t.co/9Lnfc8OCbt #JCOCCI https://t.co/HNzOoTNC9y
    view full post

    May 19, 2020

    3

  • Journal of Clinical Oncology
    @JCO_ASCO (Twitter)

    RT @veerab: Some non-covid news; our work on pan-cancer network modeling of patient and cell-line interactome is finally online at @ASCO_pu…
    view full post

    May 7, 2020

    1

  • Journal of Clinical Oncology
    @JCO_ASCO (Twitter)

    RT @rupam_mmb: The first paper from my PhD research work (potentially the first chapter of my thesis) is finally online! https://t.co/azeI…
    view full post

    May 7, 2020

    2

  • Veera Baladandayuthapani
    @veerab (Twitter)

    Some non-covid news; our work on pan-cancer network modeling of patient and cell-line interactome is finally online at @ASCO_pubs JCO-CCI. A tremendous effort led by @rupam_mmb and Min Jin Ha. Also check out our Shiny app https://t.co/eFlKnxcyE4 https://t.co/jRM0QI6OC0
    view full post

    May 7, 2020

    13

    1

  • Rupam Bhattacharyya
    @rupam_mmb (Twitter)

    The first paper from my PhD research work (potentially the first chapter of my thesis) is finally online! https://t.co/azeIntUzHU @veerab @ASCO https://t.co/TyPPJqaIpV
    view full post

    May 6, 2020

    6

    2

  • If you want to celebrate your first ever r2 defeat, please post the link ...

    https://ascopubs.org/doi/full/10.1200/CCI. 19.00140 Two reviewers, one round of solid reviews and submission to publication in six months ...
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    August 2, 2022

    Facebook

  • New analytic tool designed to help guide precision oncology ...

    Reference: Journal of Clinical Oncology Clinical Cancer Informatics, doi:10.1200/CCI.19.00140, published May 6, 2020. Resources: University ...
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    May 19, 2020

    News

Abstract Synopsis

  • TransPRECISE is a sophisticated modeling framework that uses Bayesian networks to analyze both patient data and cell line experiments across various cancer types, helping to identify key pathways and potential drug targets.
  • The study assessed thousands of tumor samples and cell lines, revealing similarities and differences in pathway activities, such as hormone receptor and tyrosine kinase signals, which help understand cancer behavior and how well cell lines replicate patient tumors.
  • The model was successful in classifying clinical subtypes and predicting drug responses with high accuracy, providing a valuable tool for personalized cancer treatment and drug development.