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Welcome
At Anabiosi-Data, we leverage advanced biological insights and data-driven strategies to deliver personalized cancer treatments. Our comprehensive in vivo services, including various treatment methods, are key to our approach. Combined with imaging analysis, biomarker performance, simulation & modelling, and pathway enrichment analysis, we ensure effective and tailored treatment strategies for each unique case. read more
Analysis image
Comprehensive Spatial Analysis of Tumor Biology through Image Analysis. Utilizing state-of-the-art computational pathology techniques, our team of skilled image and data analysis experts can assist you in uncovering the crucial insights from your images. Identify the existing phenotypes, discover regional variations in immune response, and comprehend the fundamental biology to guide your study design
Biomarker Performance
This service aims to provide you with insights on the potential of a biomarker as a diagnostic tool to differentiate between healthy and diseased states, a predictive tool to forecast the impact of treatment on the disease, or a prognostic marker to predict the progression of the disease regardless of treatment. The performance of a biomarker can be evaluated either individually or as a panel of multiple biomarkers. Our bioinformatics team will employ a variety of techniques, including ROC analysis, PCA, clustering, and state-of-the-art machine learning methods, to determine the optimal biomarkers. While we utilize cutting-edge computational methods, we communicate our findings in plain language for your scientific team and aim to provide biomarkers with the highest diagnostic accuracy.
Simulation & Modelling
Simulation and mathematical modeling are powerful tools that can help us better understand complex systems, including biological systems. By developing mathematical models, AnaBioSi-Data Ltd can gain insights into the behavior of biological systems and make predictions about how they will respond to different stimuli or interventions.
Mathematical models can be used to simulate the behavior of a system under different conditions, allowing researchers to test hypotheses and explore different scenarios. Statistical models can be used to analyze experimental data and identify patterns and trends that may be difficult to see with the naked eye.
In the context of AnaBioSi-Data Ltd, these tools could be used in a variety of ways. For example, they could be used to:
Model the behavior of a particular biological system, such as a cell or a tissue, in response to different drugs or environmental conditions
Develop predictive models that can be used to optimize drug dosing or treatment strategies
Analyze large data sets to identify biomarkers that could be used to diagnose or monitor disease
Design experiments that are more efficient and effective, by using simulations to identify the most informative conditions to test
Overall, the use of mathematical and statistical models can be a powerful way to gain new insights into biological systems and improve our ability to diagnose, treat, and prevent disease.
Mathematical models can be used to simulate the behavior of a system under different conditions, allowing researchers to test hypotheses and explore different scenarios. Statistical models can be used to analyze experimental data and identify patterns and trends that may be difficult to see with the naked eye.
In the context of AnaBioSi-Data Ltd, these tools could be used in a variety of ways. For example, they could be used to:
Model the behavior of a particular biological system, such as a cell or a tissue, in response to different drugs or environmental conditions
Develop predictive models that can be used to optimize drug dosing or treatment strategies
Analyze large data sets to identify biomarkers that could be used to diagnose or monitor disease
Design experiments that are more efficient and effective, by using simulations to identify the most informative conditions to test
Overall, the use of mathematical and statistical models can be a powerful way to gain new insights into biological systems and improve our ability to diagnose, treat, and prevent disease.
Pathway Enrichment Analysis
The Pathway Enrichment Analysis component employs data obtained from Proteomics or RNA or ChIP sequencing to determine functional pathways that are either upregulated or downregulated. The analysis provides a visual representation of the effect of specific treatments or conditions on the overall functional mechanisms in the target organism. The pathway analysis component is limited to commonly studied eukaryotic model organisms (e.g. human, mouse, rat) for which pathway information is accessible.
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