| Ribo-Seq Analysis |
- Footprint profiles, estimate translation efficiency,
- Predict distinct features (e.g. ORFs, Ribosome Stalling, Codon Usage Bias). |
4 |
Details |
| RNA-Seq Analysis |
- FastQC, Primer trimming, Salmon quantification.
- Quality control (e.g. Data cleaning, PCA, hierarchical clustering).
- Significance, fold-changes, Gene set / pathway enrichment analysis. |
4 |
Details |
| Data mining and datasets curation |
- Data mining on the public RNA-seq databases for cross-studies analysis, relationships exploration and validations. |
4 |
Details |
| Interactive Platform |
- Exploratory analysis graphical outputs (e.g. Correlation heatmap, Density plot, Volcano plot, MA plot); ML results (e.g. Learning curves and metrics explorations, Model architecture customizations, 3D plots) |
4 |
Details |
| Consultation |
- Meeting experts, reports, delivery of PPT and guides. |
4 |
Details |
| APIs and Server Setup |
- Setting up the docker with the required compute and storage for the project.
(Cost varies depending on the computing resource and storage sizes required) |
10 |
Details |
| ML fo gene-based optimizations |
- Key features search, Predictive modelling, Feature explanations, Transfer learning, Causal inference and optimizations. |
4 |
Details |
| Metabolomics Analysis |
- Identify significantly expressed metabolites, enrichment and pathway analysis. |
4 |
Details |
| Benchmarking AI Solutions |
- Benchmarking of the ML models performance against standard datasets and metrics for quick publish of results. |
4 |
Details |
| ML for conditional-based optimizations |
- Key features search, Predictive modelling, Feature explanations, Transfer learning, Causal inference and optimizations. |
4 |
Details |