Use OligoWalk Online
Commercially Available OligoWalk No-Code Web Server
OligoWalk: An Online siRNA Design Tool Utilizing Hybridization Thermodynamics
OligoWalk is an advanced algorithm for designing small interfering RNA (siRNA) candidate sequences using a target gene's RNA sequence.
OligoWalk enables the precise prediction and ranking of functional siRNAs by calculating the thermodynamic equilibrium states of hybridization.
How OligoWalk Works
OligoWalk is built on rigorous thermodynamic parameters that evaluate the free energy changes ΔGo involved in oligonucleotide-target interactions.
Thermodynamic Rigor: The web server calculates the free energy profiles of the equilibrium states by fully considering target mRNA self-structure as well as both unimolecular and bimolecular self-structures for the siRNA.
Support Vector Machine (SVM): Utilizing the predicted thermodynamic variables alongside local siRNA sequence features, an embedded SVM classification model predicts silencing efficacy.
Performance: The classification model is trained on a public dataset containing 2,431 experimental results in human cells. On average, the fraction of efficient siRNAs selected by the server that will achieve high silencing efficacy (greater than 70% target inhibition) is 78.6%.
What is Tamarind Bio?
Tamarind Bio is a pioneering no-code bioinformatics platform built to democratize access to powerful computational tools for life scientists and researchers. Recognizing that many cutting-edge tools and machine learning models are often difficult to deploy and use, Tamarind provides an intuitive, web-based environment that completely abstracts away the complexities of high-performance computing, software dependencies, and command-line interfaces.
Key features include a user-friendly graphical interface for setting up and launching experiments, a robust API for integration into existing research pipelines, and an automated system for managing and scaling computational resources. By handling the technical heavy lifting, Tamarind empowers researchers to concentrate on their scientific questions and accelerate the pace of discovery. The Tamarind team holds information/data security as a top priority, ensuring your data and intellectual property remain safe and isolated on the platform.
Accelerating Discovery with OligoWalk on Tamarind Bio
Using OligoWalk on a platform like Tamarind Bio accelerates knock-down workflows and therapeutic design campaigns:
Mitigating Trial and Error: Because not all siRNA duplexes successfully function in silencing, OligoWalk mitigates the significant cost and time spent on physical trial and error in the laboratory.
Streamlined Advanced Options: Expert users can instantly customize advanced options—such as altering the target binding mode (e.g., refolding target RNA), selecting ensemble partition functions, or applying sequence prefilters—directly within context-aware web forms.
Bridging In Silico and In Vitro: By accurately prioritizing the highest probability candidates first, fewer designs must be synthesized and tested in the lab, heavily reducing downstream experimental screening costs.
How to Use OligoWalk on Tamarind Bio
To leverage OligoWalk's analytical power on a platform like Tamarind Bio, a researcher can follow this streamlined workflow:
Access the Platform: Begin by logging in to the app.tamarind.bio website.
Select OligoWalk: From the list of available computational and oligonucleotide design tools, choose the OligoWalk tool.
Input Target Sequence: Provide the RNA sequence of the target gene you wish to silence (supports A, U, T, G, and C up to 10,000 nucleotides).
Adjust Custom Parameters (Optional): Define custom parameters such as oligomer length (defaulting to 19 nucleotides), oligonucleotide concentration, scan region, or folding size boundaries.
Select Folding Method: Choose your calculation mode for target self-structure, ranging from fast optimal structure predictions to highly accurate partition function calculations.
Generate Candidates: Provide an email address and hit submit. The platform automatically handles high-performance cluster computing to execute the partition function and SVM architectures.
Evaluate and Select: Review the generated output tables directly on the platform. Candidates are clearly ranked by their probability of being efficient siRNAs, paired with detailed breakdown metrics like ΔGoverall, duplex stability, and end stability differences (End_diff) to help you choose the best sequences for validation.