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Alessandra Carbone Profile
Alessandra Carbone

@acarbone16

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Computational Biology @LCQB_UMR7238 - Protein Sequences in Structure/Function/Classification, Genome Structure, Ancient Genomes & Geometry of Logical Reasoning

Joined June 2018
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@acarbone16
Alessandra Carbone
2 months
See you at Imperial College London this week!.Thank you for the kind invitation to the event!.
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@acarbone16
Alessandra Carbone
2 months
PRESCOTT online in Genome Biology! see how it works on differentiating mutational effects across isoforms, unique genetic heritage, recessive and dominant inheritance modes, gain-of-function mutations at Work done with @mtekpinar T.Henry L.David.
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@acarbone16
Alessandra Carbone
3 months
Thank you very much for the invitation to talk to ISSAID 2025. I really enjoyed the conference! looking forward to day 2 tomorrow. @ISSAID_official
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@acarbone16
Alessandra Carbone
4 months
it is online! recoding of TRX functions by switching specific functional determinants: with.@julhenri @SLemaire75 Gianluca Lombardi and Andrea Mancini.
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@acarbone16
Alessandra Carbone
5 months
As always, a particularly stimulating collaboration with @julhenri , @SLemaire75 , Gianluca Lombardi and Andrea Mancini.
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@acarbone16
Alessandra Carbone
5 months
We recoded a function of C.reinhardtii thioredoxin type-h into a photosynthetic type-f. Functional determinants (catalytic site and specific residues allowing partner selection) can be identified computationally. Soon out in Frontiers in Plant Science:
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@acarbone16
Alessandra Carbone
5 months
RT @srikosuri: It’s been a tough few weeks. My 10yo daughter was diagnosed with a very rare, aggressive cancer called interdigitating dendr….
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@acarbone16
Alessandra Carbone
5 months
great work with Gianluca Lombardi and @BeatrizSeoaneB #disorder #proteins #AF2 #alphafold.
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@acarbone16
Alessandra Carbone
5 months
Diversifying disorders by distinguishing intrinsic and soft disorders, improves our understanding of proteins. See our new preprint on "LoRA-DR-suite: adapted embeddings predict intrinsic and soft disorder from protein sequences" -
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@acarbone16
Alessandra Carbone
5 months
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@acarbone16
Alessandra Carbone
8 months
Happy to share with you "Integrative spatial and genomic analysis of tumor heterogeneity with Tumoroscope", with @ShadiShafighi, @ewa_szczurek, and . Great work Shadi!
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@acarbone16
Alessandra Carbone
9 months
Prix Nobel de chimie 2024 : design des protéines et prédiction de leurs structures, deux facettes d’une même médaille via @FR_Conversation.
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@acarbone16
Alessandra Carbone
10 months
RT @BonomiMax: Mini-symposium “AI in structural biology: What’s next ?” on November 12 2024 at @institutpasteur organised by @BardiauxB @D….
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@acarbone16
Alessandra Carbone
10 months
Thank you Eugenio De La Mora for the invitation at @IBS_Grenoble. It was an inspiring day with a lot of interesting projects going on and very engaged researchers! a great place to visit!!.
@IBS_Grenoble
Institut de Biologie Structurale
10 months
#IBSevents: Friday 13/09 at 11am, seminar by Dr Alexandra Carbone (IPBS, Sorbone-Université), entitled 'Decoding Protein Interactions and Mutational Landscapes with Deep Learning': #DeepLearning #Bioinformatics #ProteinInteractions #Biotech #AI
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@acarbone16
Alessandra Carbone
10 months
RT @hamed_khakzad: As part of my recently funded ANR-JCJC grant @AgenceRecherche, I’m looking for a postdoc researcher and an engineer with….
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@acarbone16
Alessandra Carbone
10 months
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@acarbone16
Alessandra Carbone
11 months
with Gianluca Lombardi at @Sorbonne_Univ_.@LCQB_UMR7238 - See MuLAN predicting mutational effects for Chlamydomonas TRX-f2 complexed with diversed partners:
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@acarbone16
Alessandra Carbone
11 months
For the first time, by computing binding affinity changes of interacting proteins from sequence data, we reconstruct complex-informed mutational landscapes and enhance the identification of both loss- and gain-of-function mutations. Discover MuLAN!
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@acarbone16
Alessandra Carbone
11 months
with @LaineElodie and Gianluca Lombardi at @Sorbonne_Univ_ @LCQB_UMR7238
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@acarbone16
Alessandra Carbone
11 months
Discover how GEMME delivers efficient, interpretable predictions for disordered proteins, stability, multi-mutation impacts, and functional sites. Read now.
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