Canreg5 is a software package for population based cancer registries
Cancer registries need a tool to input, store, check and analyse their data. If these data are also coded and verified in a standard way, it facilitates the production of comparable analyses across registry populations. The main goal of the CanReg5 project is to provide a flexible and easy to use tool to accomplish these objectives. CanReg5 is a multi user, multi platform, open source tool to input, store, check and analyse cancer registry data. It has modules to do: data entry, quality control, consistency checks and basic analysis of the data It was designed with an emphasis on user friendliness, it has a modern user interface and is easy to navigate. Is available in several languages. (English, French, Spanish, Portuguese, Russian, Turkish, Georgian, and Chinese.)
Chinese I Ching Algorithms implemented with R programming
I Ching offers an idea to summary the world by constructing functional mappings in finite groups. Much of ancient Chinese natural and social science grew from its concepts as root. The derived theories like "Eight Diagrams", "Five Elements" became the foundation of nearly all academic fields in acient Chinese. As a result, the theories are also the high concentration of many practical and statistical experience in China during her thousands-of-year history. This project tries to realize these algorithms with statistical programming. Overcoming the long span has important meanings. First, we can verify the validity of algorithm with big data. Second, we can put them into unprecedented wide application in the age of data. Third, the unique inspection of I Ching that linked "all the universe" open new eyes for us in thought and methodology about interdisciplinary use of data. This program is open-source for human. If you are interested in it, welcome to discuss and work together.
Weather and Climate Risk Management
A comprehensive and flexible quantification tool for proteomics data
PANDA is a comprehensive and flexib tool for quantitative proteomics data analysis, which is developed based on our solid foundations in quantitative proteomics for years. Several novelties have been implemented in it. First, we implement the advantage algorithms of LFQuant (Proteomics 2012, 12, (23-24), 3475-84) and SILVER (Bioinformatics 2014, 30, (4), 586-7) into PANDA. Second, we consider the state-of-art concept of quantification reliability in this quantitative workflow. On the levels of spectra, peptides and proteins, PANDA works out a few quantitative filters and new scores for quantification confidence. Third, PANDA is designed for processing proteomics big data in parallel.
A lot of fish in a shoal, in a gigantic scientific ocean.
Ours organization website GCModeller.org is coming online soon! Shoal Shell is the sub project for the "genome-in-code"(http://code.google.com/p/genome-in-code/) virtual cell modelling project of the bacteria Xcc 8004. Shoal Shell aim at provide the modelling tool and the debugging tool for the GCModeller virtual cell modelling, And from the extendible library package, shoal shell can manage to accomplish the entire modelling job for any other bacteria species. Shoal Shell Project needs grownup I'm just a student in the university, and the shoal shell just in its begining, if you have any idea about shoal, please contact me from firstname.lastname@example.org. The Shoal shell needs your professional advice. Try get some help (if you want build the shoal library by yourself): https://sourceforge.net/p/shoal/wiki/Shoal%20Developer%20Guide/
this project receives economy data from data source and analyses these data using clasical method
To identify the genes associated with breast cancer
This project is designed to identify a gene expression signature that is highly predictive of breast cancer. Cancer is a major subject matter of biomedical research but identification of the breast cancer related genes is very difficult for a small set of samples. Biological systems such as gene regulatory networks will help us detect the breast cancer related genes and understand the complex biological process in a systematic way. However, the construction of such a gene regulatory network is very challenging for a high-dimensional situation.
This project is goaled a r-language wrap of Artificial Neural Network library libfann. also known as R-binding libfann
My personal utilities wrote for dealing with Science and Computational Chemistry Jobs.