More adjustments

Author: Aaron Meyer

research/industry.md

@@ -3,7 +3,7 @@ layout: page
 title: Industry Consulting & Collaboration
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-#### Multivalent Binding Modeling for Therapeutic Design Optimization
+### Multivalent Binding Modeling for Therapeutic Design Optimization
 
 Our lab offers advanced multivalent binding modeling services to help biotechnology companies optimize the design of multi-specific immunotherapeutic agents. Using a flexible multivalent binding framework (relevant publications), we can:
 
@@ -21,39 +21,32 @@ Our services include:
 
 We work closely with clients to address specific scientific questions and provide actionable insights for therapeutic design optimization. We have worked with several organizations, from early startups to large pharmaceutical organizations, both as a grant or work for hire. Our expertise can help accelerate your drug development process and improve candidate selection.
 
-Relevant publications:
+#### Relevant Publications
 
 {% bibliography --query @*[keywords ~= binding] %}
 
 
-#### Tensor Modeling and Big Data Exploration
+### Tensor Modeling and Big Data Exploration
 
 <img src="RISE.svg" width="100%" />
 
-Our lab specializes in applying innovative tensor-based approaches to analyze complex, multidimensional biological datasets that traditional matrix methods cannot adequately address. By leveraging tensor decomposition techniques, we help researchers extract meaningful patterns and relationships from high-dimensional biomedical data.
-
-## Our Tensor Analysis Services Include:
-
-- **Multidimensional Data Transformation**: Converting conventional datasets into tensor structures that preserve the natural relationships between experimental dimensions (e.g., drug concentration, time points, cell types, and molecular features)
-
-- **Custom Tensor Decomposition Algorithms**: Developing specialized algorithms tailored to the unique characteristics of biomedical data, including handling missing values, incorporating biological constraints, and accounting for noise
-
-- **Interpretable Feature Extraction**: Identifying key factors and interactions across multiple dimensions that drive biological phenomena, making complex results accessible to domain experts
-
-- **Integration of Multi-Omic Data**: Combining diverse data types (genomics, proteomics, metabolomics, etc.) within unified tensor frameworks to reveal cross-platform patterns
-
-- **Scalable Implementations**: Creating efficient computational solutions for large-scale datasets that balance statistical rigor with practical usability
-
-## Benefits for Biomedical Research:
+Our lab specializes in applying innovative tensor-based approaches to analyze complex, multidimensional biological datasets that traditional matrix methods cannot adequately address. By leveraging tensor decomposition techniques, we help researchers extract meaningful patterns and relationships from high-dimensional biomedical data. These techniques offer several substantial benefits to biomedical data analysis:
 
 - Preservation of data structure and relationships that would be lost in matrix-based approaches
 - Increased statistical power through proper modeling of experimental design
 - Discovery of higher-order interactions not detectable with standard methods
 - Reduction in dimensionality while maintaining interpretability
 - Robust handling of sparse, noisy, or incomplete datasets common in biological studies
 
+Our potential services include:
+
+- **Multidimensional Data Transformation**: Converting conventional datasets into tensor structures that preserve the natural relationships between experimental dimensions (e.g., drug concentration, time points, cell types, and molecular features)
+- **Custom Tensor Decomposition Algorithms**: Developing specialized algorithms tailored to the unique characteristics of biomedical data, including handling missing values, incorporating biological constraints, accounting for noise, and ensuring scalability
+- **Interpretable Feature Extraction**: Identifying key factors and interactions across multiple dimensions that drive biological phenomena, making complex results accessible to domain experts
+- **Integration of Multi-Omic Data**: Combining diverse data types (genomics, proteomics, metabolomics, etc.) within unified tensor frameworks to reveal cross-platform patterns
+
 Our team works collaboratively with clients to implement these advanced analytical approaches, providing accessible software tools, comprehensive documentation, and expert consultation to ensure tensor methods enhance your research capabilities.
 
-Relevant publications:
+#### Relevant Publications
 
 {% bibliography --query @*[keywords ~= tensors] %}