@@ -12,12 +12,7 @@ export function Contribution() {
sequences, which is always available.
</p>
<p>
Using machine learning, we aim to develop an efficient prediction
software that takes the DNA sequences and half-life features as input
and outputs the mean score expression (MSE) to assist medical
professionals in determining the right approach to creating personalized
vaccines for patients. Professionals can use our software to see if the
selected neoantigen is suitable for vaccine development.
We propose using machine learning to develop an efficient prediction software that takes DNA sequences (promoters) and half-life features as input and outputs the mean score expression (MSE) to assist medical professionals in determining the right approach to creating personalized vaccines which deliver the appropriate neoantigen. Professionals can use our software to see if the selected neoantigen is suitable for vaccine development.
</p>
<p>
Our project can contribute to IGEM by providing dataset sources that we
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@@ -131,9 +126,9 @@ export function Contribution() {
</p>
<h4>Model</h4>
<p>
Our team worked towards making our project accessible to other igem
Our team worked towards making our project accessible to other IGEM
teams. Firstly, we ensure that other teams can run our code through our
Gitlab, which consists of instructions that other teams can follow and
Gitlab, which consists of detailed instructions that other teams can follow and
can implement the code for further development. Using our code and
GitLab, teams can gain our model’s architecture and the code that we use
to develop the model. Teams can run our model by reading our in-code
