#RNA #Biotechnology #ViennaRNA #ComputationalBiology
8/n
#RNA #Biotechnology #ViennaRNA #ComputationalBiology
8/n
For instance, using more than 600 #tRNA sequences from tRNAdb, we've shown how modified bases significantly impact predicted structures.
#Bioinformatics #SyntheticBiology
7/n
For instance, using more than 600 #tRNA sequences from tRNAdb, we've shown how modified bases significantly impact predicted structures.
#Bioinformatics #SyntheticBiology
7/n
#NucleotideModifications #RNAComputing
6/n
#NucleotideModifications #RNAComputing
6/n
We don't rely on a pre-compiled, complete set of energy parameters for modified bases. Instead, we use a mix of hard- and soft-constraints to adjust predictions where we have parameters.
#RNAScience #RNABioinformatics
5/n
We don't rely on a pre-compiled, complete set of energy parameters for modified bases. Instead, we use a mix of hard- and soft-constraints to adjust predictions where we have parameters.
#RNAScience #RNABioinformatics
5/n
#Inosine (I)
#Pseudouridine (P)
#N6-methyladenosine (m6A)
#7-deaza-adenosine (7DA)
#Nebularine (purine)
#Dihydrouridine (D)
#Bioinformatics #ComputationalBiology #RNAStructure #SyntheticBiology
4/n
#Inosine (I)
#Pseudouridine (P)
#N6-methyladenosine (m6A)
#7-deaza-adenosine (7DA)
#Nebularine (purine)
#Dihydrouridine (D)
#Bioinformatics #ComputationalBiology #RNAStructure #SyntheticBiology
4/n
#ViennaRNA
3/n
#ViennaRNA
3/n
#RNAResearch #RNAEditing #LifeSciences
2/n
#RNAResearch #RNAEditing #LifeSciences
2/n