proteomics made accessible
SoCal Bioinformatics provides consulting services that support the entire proteomic biomarker discovery process, from raw data processing to predictive modeling. We work with clients at any point in the process to ensure research and development have the greatest chance at success.
From patient stratification to laboratory work flow, SCBI has helped clients develop processes to ensure quality data is generated from the beginning.
With existing data SCBI can apply proprietary tools to reduce variability, expand biological coverage and filter outlier data prior to statistical analysis.
Using advanced machine learning techniques and custom discovery pipelines, SCBI can find the signal hidden among the biological noise.
Efforts in discovering biomarkers from liquid biopsies with sufficient performance to be clinically useful remain a significant challenge in diagnostics. However, as detailed in this example, researchers can leverage highly multiplexed approaches to simultaneously measure a multitude of proteins.Continue reading
Building predictive models that successfully generalize to new data is a challenging process full of potential pitfalls. During the modeling building process, cross-validation is routinely used to optimize parameters, and importantly, provide an independent assessment of trained model performance using the hold-out test set partitions.Continue reading