A BIOLOGICAL ENGINE &
COMPUTATIONAL TOOL

We love Sibe and the work Sibe does. We work closely with our
colleagues to deliver the best possible solutions for their research.

What is Sibe

Sie is a powerful digital engine, it can be used for biological science, particularly in protein folding & design, genomics, statistical calculation, deep learning, and optimization.

Sibe is an analytical and computational framework, and it aims to provide a powerful tool for biological science, such as sequence data analysis, in silico protein folding and design. Though much of the software suite is oriented toward basic research on protein sequence analysis, folding and design, Sibe is also designed for extracting meaningful information hidden behind `big data' based on machine learning. With the help of statistical analysis methods, Sibe can infer co-evolutionary information encoded in protein amino acids sequences for protein folding and design. Now, Sibe includes seven easy-interfaced modules, several physical- & chemical-principles and statistical analysis methods, as well as different optimization solvers.

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WE BELIEVE IN GREAT IDEAS

The success of the software depends in part on the co-evolution derived method for detecting amino acid variations, and the easy-interface modules presented in Sibe lay the groundwork for drawing interpretable conclusions from protein sequence data to its folding and design studies in silico.

Generally, Sibe's power and perspicuous architecture are dependent on expressive and functional modules, which focus on extending methods specifically designed for the scientific applications in biophysics.

What Sibe does

Sibe can provide an easy and rapid way for protein folding and design from analytical and computational inferences on protein sequences.

Protein Design

Computational protein design
Statistical inference
Co-Evolutionary information

Genomics

Statistical analysis
Functional genomics
Structural genomics

Protein Folding

Folding simulation
Folding pathways
Folding status

Protein Structure Prediction

Residue-Contact prediction
Secondary structure prediction
Tertiray structure prediction

Statistics

Analysis
Calculations
Demonstrations

Individulized Modeling

Customized mathematical model
Data-driven model
Optimized model

Deep learning

Deep neural networks
Auto-generated networks
Deep learner

Optimization

Quasi-Newton algorithms
Swarm intelligence
Monte Carlo methods

We develop a delightful computational tool.

Read more about what sibe does and our services.

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