This is a repository for project 'Prediction of protein secondary structure from sequence by Hiddem Markov Model(HMM) method' for a course 'MOL3022- Bioinformatics - Method Oriented Project' at NTNU, in spring 2019.
There are many folders and files, but only 'final' folder is related to the complete program.
- hiddenmarkovmodel.py -- main file
- statistics.py-- module file
- sequence.py -- module file
- mathematics.py -- module file
- Download all files in /final/windows/ folder and unzip.
- Excecute hiddenmarkovmodel.exe file.
- Type file directory for training and testing.
- Output files (decoded sequence) are saved at output folder. (Caution! 'output' folder MUST exist for saving.)
- Download all files in /final/linux/ folder unzip.
- Input files MUST be in same folder with hiddenmarkovmodel.py
- Type terminal command below at the directory that you have four .py files mentioned above.
chmod u+x hiddenmarkovmodel.py
- Type terminal command below for executing.
./hiddenmarkovmodel.py
- Output files are saved in same directory with hiddenmarkovmodel.py
- hiddenmarkovmodel.py -- main file -- last update 01 Aug, 2019
- statistics.py-- module file -- last update 22 Mar, 2019
- sequence.py -- module file -- last update 01 Aug, 2019
- mathematics.py -- module file -- last update 25 Mar, 2019
- protein-secondary-structure.train -- for training, 111 sets
- protein-secondary-structure.test -- for testing, 17 sets
- raw_data_simpleHMM.csv
- raw_data_EMHMMconv.csv
- raw_data_EMHMMiter.csv
- Jones, D.T.: Protein secondary structure prediction based on position-speci c scoring matrices. Journal of molecular biology 292(2), 195{202 (1999)
- Example Diagram of HMM. http://yanfenglu.net/researchVAS_p1.htm
- Abela, J., Michael, J.: Topics in evolving transformation systems [microform]. (2019)
- Sheh, A., Ellis, D.P.: Chord segmentation and recognition using em-trained hidden markov models (2003)
- Bayes Theorem. https://www.britannica.com/topic/Bayess-theorem
- Hidden Markov Models. https://archive.ics.uci.edu/ml/datasets/Molecular+Biology+(Protein+Secondary+Structure)
- Qian, N., Sejnowski, T.J.: Predicting the secondary structure of globular proteins using neural network models. Journal of molecular biology 202(4), 865{884 (1988)
- Main Program Repository of Author. https://github.com/hyejeonc
- Matlib Library. https://matplotlib.org/
- Asai, K., Hayamizu, S., Handa, K.: Prediction of protein secondary structure by the hidden markov model. Bioinformatics 9(2), 141{146 (1993)
- Boodidhi, S.: Using smoothing techniques to improve the performance of hidden markov's model (2011)
- Shifrin, J., Pardo, B., Meek, C., Birmingham, W.: Hmm-based musical query retrieval. In: Proceedings of the 2nd ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 295{300 (2002). ACM
- Landschulz, W.H., Johnson, P.F., McKnight, S.L.: The leucine zipper: a hypothetical structure common to a new class of dna binding proteins. Science 240(4860), 1759{1764 (1988)
- Soding, J.: Protein homology detection by hmm{hmm comparison. Bioinformatics 21(7), 951{960 (2004)
- Won, K.-J., Hamelryck, T., Prugel-Bennett, A., Krogh, A.: An evolutionary method for learning hmm structure: prediction of protein secondary structure. BMC bioinformatics 8(1), 357 (2007)
- Lee, L., Leopold, J.L., Frank, R.L.: Protein secondary structure prediction using blast and relaxed threshold rule induction from coverings. In: 2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), pp. 1{8 (2011). IEEE
- Protein HMM raw data files by programming tool https://github.com/dmvvliet/protein-HMMs
- hmmexample.py -- main file for predicting weather with comsumption of icecream https://github.com/jason2506/PythonHMM
- weatherexample.py -- module file, same as 18.
- COMP3212CompBiologyLabs-master -- predicting genetic code from protein sequence https://github.com/aloisklink/COMP3212CompBiologyLabs
- HMM and EM algorithm lecture pdf https://people.cs.umass.edu/~mccallum/courses/inlp2004a/lect10-hmm2.pdf
- HMM with weather example and tutorial https://sambaiga.github.io/2017/05/03/hmm-intro.html
- Baum-Welch(EM) algorithm http://www.biostat.jhsph.edu/bstcourse/bio638/notes/HMMs_BaumWelch.pdf
- Smoothing method https://danieltakeshi.github.io/2015-07-25-hidden-markov-models-and-particle-filtering/