CRV Science Labs ⚗️
🧬 Synonymous Codon Optimization and RNA Secondary-Structure Folding Benchmarked Against ViennaRNA v2.7.2 — Because 18 of the 20 standard amino acids are encoded by multiple synonymous codons, protein-coding RNA transcr…
https://crvscience.com/labs/discoveries/codon-opt-viennarna
🧬 Synonymous Codon Optimization and RNA Secondary-Structure Folding Benchmarked Against ViennaRNA v2.7.2 — Because 18 of the 20 standard amino acids are encoded by multiple synonymous codons, protein-coding RNA transcr…
https://crvscience.com/labs/discoveries/codon-opt-viennarna
CRV Science Labs ⚗️
🧬 Synonymous Codon Optimization and RNA Secondary-Structure Folding Benchmarked Against ViennaRNA v2.7.2 — Because 18 of the 20 standard amino acids are encoded by multiple synonymous codons, protein-coding RNA transcripts can vary widely in both translational efficiency and sec…
crvscience.com
November 2, 2026 at 11:36 AM
CRV Science Labs ⚗️
🧬 Synonymous Codon Optimization and RNA Secondary-Structure Folding Benchmarked Against ViennaRNA v2.7.2 — Because 18 of the 20 standard amino acids are encoded by multiple synonymous codons, protein-coding RNA transcr…
https://crvscience.com/labs/discoveries/codon-opt-viennarna
🧬 Synonymous Codon Optimization and RNA Secondary-Structure Folding Benchmarked Against ViennaRNA v2.7.2 — Because 18 of the 20 standard amino acids are encoded by multiple synonymous codons, protein-coding RNA transcr…
https://crvscience.com/labs/discoveries/codon-opt-viennarna
CRV Science Labs ⚗️
🧬 Thermodynamic RNA Folding & Partition Function Benchmark: Native Turner-2004 Zuker–McCaskill Engine vs. ViennaRNA (RNAfold v2.7.2) — Head-to-head thermodynamic calibration of our native 4-stage Turner-2004 Z…
https://crvscience.com/labs/discoveries/rna-fold-turner-vs-viennarna
🧬 Thermodynamic RNA Folding & Partition Function Benchmark: Native Turner-2004 Zuker–McCaskill Engine vs. ViennaRNA (RNAfold v2.7.2) — Head-to-head thermodynamic calibration of our native 4-stage Turner-2004 Z…
https://crvscience.com/labs/discoveries/rna-fold-turner-vs-viennarna
CRV Science Labs ⚗️
🧬 Thermodynamic RNA Folding & Partition Function Benchmark: Native Turner-2004 Zuker–McCaskill Engine vs. ViennaRNA (RNAfold v2.7.2) — Head-to-head thermodynamic calibration of our native 4-stage Turner-2004 Zuker–Stiegler MFE, McCaskill partition function, and Lorenz RNA G-quad…
crvscience.com
November 1, 2026 at 3:01 AM
CRV Science Labs ⚗️
🧬 Thermodynamic RNA Folding & Partition Function Benchmark: Native Turner-2004 Zuker–McCaskill Engine vs. ViennaRNA (RNAfold v2.7.2) — Head-to-head thermodynamic calibration of our native 4-stage Turner-2004 Z…
https://crvscience.com/labs/discoveries/rna-fold-turner-vs-viennarna
🧬 Thermodynamic RNA Folding & Partition Function Benchmark: Native Turner-2004 Zuker–McCaskill Engine vs. ViennaRNA (RNAfold v2.7.2) — Head-to-head thermodynamic calibration of our native 4-stage Turner-2004 Z…
https://crvscience.com/labs/discoveries/rna-fold-turner-vs-viennarna
I am preparing two workshops under RNA Forecast: ViennaRNA and computational RNA design, and local AI coding tools for research groups, on your own hardware so your data stays in the lab. Remote or on site, 6 to 12 people. Dates go to the waitlist first: rnaforecast.com/training/
Training, RNA Forecast | ViennaRNA and local AI tools
Two hands-on training formats for research groups, remote or on site: ViennaRNA and computational RNA design, and local AI coding tools. Both in preparation; each has a waitlist.
rnaforecast.com
October 30, 2026 at 11:17 AM
I am preparing two workshops under RNA Forecast: ViennaRNA and computational RNA design, and local AI coding tools for research groups, on your own hardware so your data stays in the lab. Remote or on site, 6 to 12 people. Dates go to the waitlist first: rnaforecast.com/training/
CRV Science Labs ⚗️
🧬 Unified 1D → 2D → 3D Nucleic Acid Structural Prediction: Benchmarking DNA & RNA Folding Against ViennaRNA, RNAPKplex, and US-align — We wire and calibrate an end-to-end 1D → 2D → 3D structural prediction pipeline for DN…
https://crvscience.com/labs/discoveries/rna-dna-1d-2d-3d
🧬 Unified 1D → 2D → 3D Nucleic Acid Structural Prediction: Benchmarking DNA & RNA Folding Against ViennaRNA, RNAPKplex, and US-align — We wire and calibrate an end-to-end 1D → 2D → 3D structural prediction pipeline for DN…
https://crvscience.com/labs/discoveries/rna-dna-1d-2d-3d
CRV Science Labs ⚗️
🧬 Unified 1D → 2D → 3D Nucleic Acid Structural Prediction: Benchmarking DNA & RNA Folding Against ViennaRNA, RNAPKplex, and US-align — We wire and calibrate an end-to-end 1D → 2D → 3D structural prediction pipeline for DNA and RNA across 9 calibration loci (7 RCSB PDB crystal/Cr…
crvscience.com
November 1, 2026 at 5:01 AM
CRV Science Labs ⚗️
🧬 Unified 1D → 2D → 3D Nucleic Acid Structural Prediction: Benchmarking DNA & RNA Folding Against ViennaRNA, RNAPKplex, and US-align — We wire and calibrate an end-to-end 1D → 2D → 3D structural prediction pipeline for DN…
https://crvscience.com/labs/discoveries/rna-dna-1d-2d-3d
🧬 Unified 1D → 2D → 3D Nucleic Acid Structural Prediction: Benchmarking DNA & RNA Folding Against ViennaRNA, RNAPKplex, and US-align — We wire and calibrate an end-to-end 1D → 2D → 3D structural prediction pipeline for DN…
https://crvscience.com/labs/discoveries/rna-dna-1d-2d-3d
No more external dependency for structure plots. rf-fold now draws secondary structure plots natively, including an option to color bases on a continuous reactivity gradient. ViennaRNA RNAplot is no longer required. (6/n)
October 9, 2026 at 8:53 AM
No more external dependency for structure plots. rf-fold now draws secondary structure plots natively, including an option to color bases on a continuous reactivity gradient. ViennaRNA RNAplot is no longer required. (6/n)
【後援イベント】分子ロボティクス 夏の学校2026 🧬
分子ロボEXが後援する、分子ロボティクス研究会主催のオンライン講座です。分子ロボティクスの設計・解析ソフトウェアを手を動かして学ぶ形式で、オンデマンド講義9本（講義0〜8）と、Python・caDNAno・ViennaRNA・Visual DSD・ImageJの演習5回（Zoom）で構成。参加費無料、非会員も参加可。
📅 9/17(木)19:00〜 ガイダンス
▶申込 molbot.org/ja/event-cat...
#分子ロボEX
分子ロボEXが後援する、分子ロボティクス研究会主催のオンライン講座です。分子ロボティクスの設計・解析ソフトウェアを手を動かして学ぶ形式で、オンデマンド講義9本（講義0〜8）と、Python・caDNAno・ViennaRNA・Visual DSD・ImageJの演習5回（Zoom）で構成。参加費無料、非会員も参加可。
📅 9/17(木)19:00〜 ガイダンス
▶申込 molbot.org/ja/event-cat...
#分子ロボEX
夏の学校 2026
ガイダンス ：2026年9月17日（木）日本時間 19:00〜 ソフトウェア演習 ：9月24日（木）〜10月22日（木） 毎週木曜(日本時間の19-21時)・全5回 形式 ：講義はオンデマンド動画、演習はZoom 参加費 ：無料（事前登録が必要です） 参加登録...
molbot.org
September 10, 2026 at 12:20 AM
【後援イベント】分子ロボティクス 夏の学校2026 🧬
分子ロボEXが後援する、分子ロボティクス研究会主催のオンライン講座です。分子ロボティクスの設計・解析ソフトウェアを手を動かして学ぶ形式で、オンデマンド講義9本（講義0〜8）と、Python・caDNAno・ViennaRNA・Visual DSD・ImageJの演習5回（Zoom）で構成。参加費無料、非会員も参加可。
📅 9/17(木)19:00〜 ガイダンス
▶申込 molbot.org/ja/event-cat...
#分子ロボEX
分子ロボEXが後援する、分子ロボティクス研究会主催のオンライン講座です。分子ロボティクスの設計・解析ソフトウェアを手を動かして学ぶ形式で、オンデマンド講義9本（講義0〜8）と、Python・caDNAno・ViennaRNA・Visual DSD・ImageJの演習5回（Zoom）で構成。参加費無料、非会員も参加可。
📅 9/17(木)19:00〜 ガイダンス
▶申込 molbot.org/ja/event-cat...
#分子ロボEX
Until a fix will be released, we advice users to install ViennaRNA v2.7.0 in a separate folder and to provide the path to RNAplot v2.7.0 via the -vrp parameter of rf-fold. (4/n)
October 13, 2025 at 12:47 PM
Until a fix will be released, we advice users to install ViennaRNA v2.7.0 in a separate folder and to provide the path to RNAplot v2.7.0 via the -vrp parameter of rf-fold. (4/n)
!!! Important note: A bug was introduced in ViennaRNA v2.7.0, which breaks the pseudoknot detection functionality of rf-fold. However, RNAplot v2.7.0 is required to take advantage of the new secondary structure plotting functionality. (3/n)
October 13, 2025 at 12:47 PM
!!! Important note: A bug was introduced in ViennaRNA v2.7.0, which breaks the pseudoknot detection functionality of rf-fold. However, RNAplot v2.7.0 is required to take advantage of the new secondary structure plotting functionality. (3/n)
Highlights: new normalization method in rf-norm (Mitchell method, pubmed.ncbi.nlm.nih.gov/37334863/), statistics plots in rf-count & rf-count-genome, and secondary structure plots in rf-fold (powered by ViennaRNA v2.7.0) (2/n)
October 13, 2025 at 12:47 PM
Highlights: new normalization method in rf-norm (Mitchell method, pubmed.ncbi.nlm.nih.gov/37334863/), statistics plots in rf-count & rf-count-genome, and secondary structure plots in rf-fold (powered by ViennaRNA v2.7.0) (2/n)
Finally reading this paper; I was suprised to learn that there's no known nearest-neighbour energy parameters for two paired modified bases! Surely @moderna_tx has something they can share?
Modified RNAs and predictions with the ViennaRNA Package...
Modified RNAs and predictions with the ViennaRNA Package...
December 3, 2024 at 6:17 AM
Finally reading this paper; I was suprised to learn that there's no known nearest-neighbour energy parameters for two paired modified bases! Surely @moderna_tx has something they can share?
Modified RNAs and predictions with the ViennaRNA Package...
Modified RNAs and predictions with the ViennaRNA Package...
#RNABenasque ER: ViennaRNA has ~14k parameters, G6 has only 21. Surprisingly folding accuracy is 54% vs 48%. Or does it only have >1k?
November 17, 2024 at 10:23 AM
#RNABenasque ER: ViennaRNA has ~14k parameters, G6 has only 21. Surprisingly folding accuracy is 54% vs 48%. Or does it only have >1k?
#RNABenasque ER: Tornado grammars reproduce ViennaRNA and Contrafold scoring systems; but did also train these models.
November 17, 2024 at 10:23 AM
#RNABenasque ER: Tornado grammars reproduce ViennaRNA and Contrafold scoring systems; but did also train these models.
ViennaRNA Package v2.7.1 is out! 🧬🎉 Solid update: smoother probing-informed folding (SHAPE/DMS), improved constraints handling, and nicer Python multistrand base-pair probs.
Get: tbi.univie.ac.at/RNA/
Source: github.com/ViennaRNA/Vi...
#ViennaRNA #RNA #ComputationalBiology #SHAPE #DMS #OpenSource
Get: tbi.univie.ac.at/RNA/
Source: github.com/ViennaRNA/Vi...
#ViennaRNA #RNA #ComputationalBiology #SHAPE #DMS #OpenSource
tbi.univie.ac.at
December 7, 2025 at 9:25 PM
ViennaRNA Package v2.7.1 is out! 🧬🎉 Solid update: smoother probing-informed folding (SHAPE/DMS), improved constraints handling, and nicer Python multistrand base-pair probs.
Get: tbi.univie.ac.at/RNA/
Source: github.com/ViennaRNA/Vi...
#ViennaRNA #RNA #ComputationalBiology #SHAPE #DMS #OpenSource
Get: tbi.univie.ac.at/RNA/
Source: github.com/ViennaRNA/Vi...
#ViennaRNA #RNA #ComputationalBiology #SHAPE #DMS #OpenSource
Got interested? Read the full story here: academic.oup.com/bioinformati...
#RNA #Biotechnology #ViennaRNA #ComputationalBiology
8/n
#RNA #Biotechnology #ViennaRNA #ComputationalBiology
8/n
Modified RNAs and predictions with the ViennaRNA Package
AbstractMotivation. In living organisms, many RNA molecules are modified post-transcriptionally. This turns the widely known four-letter RNA alphabet ACGU
academic.oup.com
January 18, 2025 at 9:34 PM
Got interested? Read the full story here: academic.oup.com/bioinformati...
#RNA #Biotechnology #ViennaRNA #ComputationalBiology
8/n
#RNA #Biotechnology #ViennaRNA #ComputationalBiology
8/n
What makes the #ViennaRNA Package unique? 🤔
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
January 18, 2025 at 9:34 PM
What makes the #ViennaRNA Package unique? 🤔
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
Did you know? The #ViennaRNA Package can handle a wide range of RNA modifications, including:
#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
January 18, 2025 at 9:33 PM
Did you know? The #ViennaRNA Package can handle a wide range of RNA modifications, including:
#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
They play vital roles in regulating gene expression by influencing processes like splicing, stability, and translation. To truly understand cellular processes and disease mechanisms, we must explore how these modifications shape RNA structure and function.
#ViennaRNA
3/n
#ViennaRNA
3/n
January 18, 2025 at 9:33 PM
They play vital roles in regulating gene expression by influencing processes like splicing, stability, and translation. To truly understand cellular processes and disease mechanisms, we must explore how these modifications shape RNA structure and function.
#ViennaRNA
3/n
#ViennaRNA
3/n
YES. Gonna do some adversarial audits but so far its 1to1 with ViennaRNA. Then will tackle the tedium of UI jank. Yay, vibecoding!
June 7, 2026 at 4:39 PM
YES. Gonna do some adversarial audits but so far its 1to1 with ViennaRNA. Then will tackle the tedium of UI jank. Yay, vibecoding!
To achieve true 100% coverage, we must pass a target sequence through an RNA folding algorithm (like mfold or ViennaRNA) to identify "open," single-stranded loops or unstructured regions that are biophysically accessible to the dCas13d ribonucleoprotein.
June 15, 2026 at 12:52 AM
To achieve true 100% coverage, we must pass a target sequence through an RNA folding algorithm (like mfold or ViennaRNA) to identify "open," single-stranded loops or unstructured regions that are biophysically accessible to the dCas13d ribonucleoprotein.
MIMIC also treats experimental context as a first-class modality.
Given assay + cellular context in natural language, it predicts condition-specific RNA reactivity better than sequence-only baselines, improving downstream RNA structure modeling.
Given assay + cellular context in natural language, it predicts condition-specific RNA reactivity better than sequence-only baselines, improving downstream RNA structure modeling.
April 28, 2026 at 7:35 PM
MIMIC also treats experimental context as a first-class modality.
Given assay + cellular context in natural language, it predicts condition-specific RNA reactivity better than sequence-only baselines, improving downstream RNA structure modeling.
Given assay + cellular context in natural language, it predicts condition-specific RNA reactivity better than sequence-only baselines, improving downstream RNA structure modeling.