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Many discussions focus on the strengths of the iPHoP framework, including its ability to improve host predictions for viruses and its innovative use of machine learning. Phrases like 'showing far better performance' and discussions about addressing 'crucial gaps' indicate an enthusiastic tone and a recognition of the framework's promising applications. The choice of positive and assertive language suggests a strong belief in its utility and significance in the field.
The majority of posts indicate support for the ideas presented in the publication, highlighting its innovative approach to virus-host prediction.
There is a high level of curiosity, as many users express enthusiasm and inquiry about the new framework and its implications.
While some posts provide additional commentary on the methods used, the depth of engagement remains moderate, with users not deeply delving into detailed analysis.
Several contributors believe that the iPHoP framework has significant potential to advance research in metagenomics and virology.
#Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is lost. @simroux_virus &co present iPHoP, a new tool to maximize host prediction for #metagenome-assembled virus genomes #PLOSBiology https://t.co/151fqNwKuT https://t.co/WftLzGXKzZ
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://t.co/ynm9MByLPj
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/JOdOhk81KY
iPHoP: predict the host #taxonomy for a diverse range of viruses infecting bacteria and archaea using metagenome-derived virus genomes, with low false discovery rate and high precision and recall. [co-authored by EVBC members @simroux_virus @BEDutilh] https://t.co/vXcJnwRvsI
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://t.co/c3vfxVrTxh #biorxiv_micrbio
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/RPj2u8ZKE3
iPHoP is a new machine learning framework designed to improve host predictions for viruses infecting bacteria and archaea using metagenomic data. This approach combines multiple methods to enhance accuracy when…
@simroux_virus @simroux_virus: How do we link viruses to hosts? Many tools to predict hosts. Use all of them and put it into a magical AI/machine learning: iPHoP https://t.co/Geb9YWpqv3 #SocialViruses
RT @EVirusBioinfC: iPHoP: predict the host #taxonomy for a diverse range of viruses infecting bacteria and archaea using metagenome-derived…
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/KJ1qciJnUy https://t.co/ZGg5lWa6ds
RT @GB13Faithless: And with his integrated approach iPHoP showing far better performance due to 1) including phage based methods (rafah @…
RT @GB13Faithless: And with his integrated approach iPHoP showing far better performance due to 1) including phage based methods (rafah @…
RT @vivek_mutalik: Details different method limitations in Phage host predictions & how using integrated machine learning method just publi…
And with his integrated approach iPHoP showing far better performance due to 1) including phage based methods (rafah @linsalrob) 2) a massive host database https://t.co/RvBHtpHcpG https://t.co/AU7R6fN9X5
Details different method limitations in Phage host predictions & how using integrated machine learning method just published addresses crucial gaps @PLOSBiology https://t.co/BtIHgUmELY
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RT @EVirusBioinfC: iPHoP: predict the host #taxonomy for a diverse range of viruses infecting bacteria and archaea using metagenome-derived…
RT @EVirusBioinfC: iPHoP: predict the host #taxonomy for a diverse range of viruses infecting bacteria and archaea using metagenome-derived…
RT @EVirusBioinfC: iPHoP: predict the host #taxonomy for a diverse range of viruses infecting bacteria and archaea using metagenome-derived…
RT @EVirusBioinfC: iPHoP: predict the host #taxonomy for a diverse range of viruses infecting bacteria and archaea using metagenome-derived…
RT @EVirusBioinfC: iPHoP: predict the host #taxonomy for a diverse range of viruses infecting bacteria and archaea using metagenome-derived…
RT @EVirusBioinfC: iPHoP: predict the host #taxonomy for a diverse range of viruses infecting bacteria and archaea using metagenome-derived…
iPHoP: predict the host #taxonomy for a diverse range of viruses infecting bacteria and archaea using metagenome-derived virus genomes, with low false discovery rate and high precision and recall. [co-authored by EVBC members @simroux_virus @BEDutilh] https://t.co/vXcJnwRvsI
RT @ShareefDabdoub: iPHoP is out in PLoS Biology! Host prediction for uncultivated viruses using #MachineLearning https://t.co/j1dM2FcGZO…
RT @ShareefDabdoub: iPHoP is out in PLoS Biology! Host prediction for uncultivated viruses using #MachineLearning https://t.co/j1dM2FcGZO…
iPHoP is out in PLoS Biology! Host prediction for uncultivated viruses using #MachineLearning https://t.co/j1dM2FcGZO #metagenomics #phage #Bioinformatics
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/J7fX7qKbTE #ai #health
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @hlcao: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacter…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
#Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is lost. @simroux_virus &co present iPHoP, a new tool to maximize host prediction for #metagenome-assembled virus genomes #PLOSBiology https://t.co/151fqNwKuT https://t.co/TcBXbOXLL8
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
#Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is lost. @simroux_virus &co present iPHoP, a new tool to maximize host prediction for #metagenome-assembled virus genomes #PLOSBiology https://t.co/151fqNwKuT https://t.co/1aRcav1v7S
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @hlcao: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacter…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
#PLOSBiology: iPHoP: An integrated #machine #learning #framework to maximize #host prediction for #metagenome-derived #viruses of #archaea and #bacteria https://t.co/2E6hWG5Y4A
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria | PLOS Biology https://t.co/xF2NMR4FSi
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria | PLOS Biology https://t.co/U2gBtpaTKi
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @PLOSBiology: #Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is l…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
RT @jcamthrash: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and b…
#Viruses infecting #bacteria & #archaea are often identified via metagenomics, but information regarding #phage hosts is lost. @simroux_virus &co present iPHoP, a new tool to maximize host prediction for #metagenome-assembled virus genomes #PLOSBiology https://t.co/151fqNwKuT https://t.co/WftLzGXKzZ
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/JOdOhk81KY
RT @pacyc1841: » iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and…
RT @metagenomic_lit: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea…
[PubMed] iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/q77C4rGL97
» iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria | PLOS Biology https://t.co/jp2tkQzidi
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria - https://t.co/tst7AKeYFX -
RT @metagenomic_lit: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea…
RT @metagenomic_lit: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea…
RT @metagenomic_lit: iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea…
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/lLzsw292Kg
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/ek5u3YWtrt https://t.co/UkIIXTEF7Q
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/RPj2u8ZKE3
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria https://t.co/2WV60yDaJt
RT @hiraokas302: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https:/…
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes | bioRxiv https://t.co/tGa347patU
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://t.co/UIUj6pFgTt
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://t.co/ZPsMxVE8pL
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes - https://t.co/D5usNOAHPO - #machinelearning
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
RT @jcamthrash: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://…
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://t.co/ynm9MByLPj
RT @biorxiv_micrbio: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes ht…
RT @biorxiv_micrbio: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes ht…
RT @biorxiv_micrbio: iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes ht…
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://t.co/owxUVTv0iT
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://t.co/AbZAlNU65m
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://t.co/KLTV4nlQVq #bioRxiv
iPHoP: an integrated machine-learning framework to maximize host prediction for metagenome-assembled virus genomes https://t.co/c3vfxVrTxh #biorxiv_micrbio