CIBB’s main goal is to provide a multidisciplinary forum for researchers interested in the
application of computational intelligence, in a broad sense, to open problems in bioinformatics,
biostatistics, systems and synthetic biology, and medical informatics. This year's in-person
meeting will bring together researchers from the international scientific community interested
in advancements and future perspectives in bioinformatics, biostatistics, and medical
informatics. CIBB is also looking for contributions on current trends and future opportunities
at the interface between computer and life sciences, and applications of computational
intelligence to system and synthetic biology. Theoretical and experimental biologists are also
encouraged to participate and present their experience in facing novel challenges to foster
multidisciplinary collaboration.
Authors are invited to submit a short paper (4-6 pages) describing their original contribution
in the fields of bioinformatics, biostatistics, systems and synthetic biology, and medical
informatics. All accepted contributions will be presented in plenary oral sessions and special
sessions. Authors of accepted short papers are encouraged to post their short papers on preprint
servers such as arXiv, bioRxiv, or medRxiv.
After the conference, the authors of all the accepted short papers presented at the
conference
will be invited to submit an extended version of their manuscripts to the conference
proceedings
book in Springer
Lecture Notes in Bioinformatics (LNBI), or to a supplement in a journal such as
BMC Bioinformatics or BMC Medical Informatics and Decision Making.
CIBB 2023 will take place on September 6-8 2023, in Padova, Italy, at the Multifunctional Psychology Hub of the University of Padova (Cittadella dello Studente, Via Venezia, 16, 35131 Padova PD). Padova is in a strategic location, just 40 km from Venice and its artistic treasures.
The final programme of the conference will include keynotes, a main track, and several special sessions. Each oral presentation is expected to last up to 15 minutes.
For any question, please contact the main conference chairs via email at cibb2023(AT)dei.unipd.it
📢RSG-Italy young symposium for #CIBB2023
— sysbiobigunipd (@sysbiobigunipd) May 31, 2023
⏰Need More Time?
Good news! @RSGItOfficial extended its deadline!
This is your chance to seize the spotlight and showcase your incredible research.
🗓️Extended Deadline: 30 June 2023
🔗Submission Guidelines: https://t.co/KiS1FXNrxI
3️⃣of 3️⃣: #CIBB2023 keynote speakers!
— sysbiobigunipd (@sysbiobigunipd) May 18, 2023
We are honoured to host Jessica Barrett from @Cambridge_Uni in #Padova!
📉💡Don't miss her enlightening talk about #biostatistics applied to #dynamic #healthdata!
Follow us to stay updated! 😉 pic.twitter.com/D8L6tAjIN8
2️⃣ of 3️⃣: Meet the #CIBB2023 keynote speakers!
— sysbiobigunipd (@sysbiobigunipd) May 10, 2023
We are thrilled to announce that @ariannadagliati will join #CIBB2023 as a keynote speaker! 📈💻#MachineLearning #PrecisionMedicine #patterns #longitudinalclinicaldata
Don't miss the final keynote speaker announcement! pic.twitter.com/v9FBBrbEl5
1⃣ of 3⃣: Meet the #CIBB2023 keynote speakers!
— sysbiobigunipd (@sysbiobigunipd) May 3, 2023
We can't wait to hear @bzupan's insights at the conference 📊🧬#ArtificialIntelligence #MachineLearning #XAI #Datavisualization #DataMining
Stay tuned to discover the other keynote speakers! pic.twitter.com/0740Z6AxFA
#CIBB2023 collaborates with @RSGItOfficial for organising short sessions of flash talks where early researcher can present their work.
— sysbiobigunipd (@sysbiobigunipd) April 28, 2023
👩💻 Submit your short abstract (max 350 words) by 31/05: https://t.co/KiS1FXNrxI#bioinformatics #computationalbiology #machinelearning #omics
📢Deadline extension📢
— sysbiobigunipd (@sysbiobigunipd) April 26, 2023
Due to numerous requests, the #CIBB2023 organising committee approved an extension of the submission deadline to May 15. You still have time to submit your innovative works! Find the guidelines here: https://t.co/TTuDrYc3C5#bioinformatics #machinelearning