Andrea Poletti (@andreapoletti19) 's Twitter Profile
Andrea Poletti

@andreapoletti19

Bioinformatician PhD student @Unibo.
Visiting scientist @DanaFarber and @BroadInstitute.
Studying #MM genomics for new insights and personalized medicine.

ID: 2980203441

calendar_today15-01-2015 19:22:16

6 Tweet

52 Takipçi

168 Takip Edilen

Università di Bologna (@unibo) 's Twitter Profile Photo

Ci sono almeno sei ceppi principali del coronavirus SARS-CoV-2, il responsabile della pandemia di COVID-19. Ma nel complesso il virus continua a mutare poco, e questa è una buona notizia in vista dello sviluppo di vaccini efficaci. magazine.unibo.it/archivio/2020/… #Unibo

Ankit Dutta (@ankitkdutta) 's Twitter Profile Photo

Excited to share our new research Cancer Discovery - MinimuMM-seq! A blood based approach for detection and WGS of circulating tumor cells for genomic profiling key myeloma biomarkers! An excellent joint effort! JB Alberge Daniel Auclair Gaddy Getz . #mmsm aacrjournals.org/cancerdiscover…

Andrea Poletti (@andreapoletti19) 's Twitter Profile Photo

Proud to have presented our work on #CopyNumberSignatures in #MultipleMyeloma at ASH 2022 in New Orleans. Such an important audience and stage encourage in pushing the limits even further! Stay tuned #ASH22 #MultipleMyeloma #Bioinformatics

Proud to have presented our work on #CopyNumberSignatures in #MultipleMyeloma at ASH 2022 in New Orleans. Such an important audience and stage encourage in pushing the limits even further! Stay tuned

#ASH22
#MultipleMyeloma 
#Bioinformatics
Robert Z. Orlowski (@myeloma_doc) 's Twitter Profile Photo

#Myeloma Paper of the Day: Multi-dimensional scaling techniques finds gain 1q & loss 13q co-occurrence identifies #myeloma patients with specific genomic, transcriptional and adverse clinical features: pubmed.ncbi.nlm.nih.gov/38378709/.

#Myeloma Paper of the Day: Multi-dimensional scaling techniques finds gain 1q & loss 13q co-occurrence identifies #myeloma patients with specific genomic, transcriptional and adverse clinical features: pubmed.ncbi.nlm.nih.gov/38378709/.
Andrea Poletti (@andreapoletti19) 's Twitter Profile Photo

🧬New study out in #NatureCommunications! New insights into Multiple #Myeloma genomic puzzle: a subset of MM patients with worse outcomes, defined by 1q gain & 13 loss could revolutionize how to classify MM, paving the way for more tailored patient care. nature.com/articles/s4146…

Andrea Poletti (@andreapoletti19) 's Twitter Profile Photo

Check out our latest publication in #NatureGenetics, where we investigate the transformation from precancerous stages to #MultipleMyeloma, introducing innovative #bioinformatic strategies to model tumor evolution and predict patient progression! doi.org/10.1038/s41588…