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Several small Bioinformatics projects implementing related algorithms, including Semi-Global alignment, Multiple Sequence Alignment using Star-Alignment, and MSA using PSSM profiles considering Gaps.

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Bioinformatics Projects

main-1: Semi-Global Alignment

This project contains an implementation of the proteins' Semi-Global alignment algorithm using dynamic programming and the PAM250 scoring matrix to score matches and mismatch penalties. For gaps, the constant penalty value is equal to 9.

Input and output formats

The inputs are two protein strings that need to be semi-globally aligned with each other. The output contains the total alignment score in the first line, and the following lines are all the possible alignment forms.

# input 

AAAAA
AA

# output

4
AAAAA
---AA
AAAAA
--AA-
AAAAA
-AA--
AAAAA
AA---

main-2: Multiple Sequence Alignment using Star-Alignment

This project contains an implementation of the proteins' Multiple Sequence Alignment algorithm, 'Star-Alignment.' The scores in this particular mini-project are equal to:

  • match: 3
  • mismatch: -1
  • gap: -2

In this project, to optimize the process, blocks containing more than or equal to two positions with at least one gap or mismatch will be chosen to be substituted and aligned with the original block repeatedly until the score doesn't get higher. In the end, the original block would be replaced by the aligned one.

Input and output formats

In the first line of the input comes the number of to-be-aligned sequences, and in the following come the sequences. The output contains the total alignment score, and after that comes the MSA.

# input 

4 
TYIMREAQYESAQ
TCIVMREAYE
YIMQEVQQER
WRYIAMREQYES

# output

51
-TYI-MREAQYESAQ
-TCIVMREA-YE---
--YI-MQEVQQER--
WRYIAMRE-QYES--

main-3: MSA using PSSM profiles

This project contains an implementation of the proteins' MSA algorithm by building a version of the PSSM profile that considers the gaps too. To avoid log(0), pseudocount = 2 is used. After building the profile, a sub-sequence from the input sequence with the highest score base on the PSSM profile would be the output.

Input and output formats

In the first line of the input comes the number of sequences in the MSA, and in the following come the sequences. In the last line comes a long sequence that the most-related sub-sequence should be detected in it (its length is at most 100.)

The output contains the desired sub-sequence.

# input 

4
HVLIP
H-MIP
HVL-P
LVLIP
LIVPHHVPIPVLVIHPVLPPHIVLHHIHVHIHLPVLHIVHHLVIHLHPIVL

# output

H-L-P

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Several small Bioinformatics projects implementing related algorithms, including Semi-Global alignment, Multiple Sequence Alignment using Star-Alignment, and MSA using PSSM profiles considering Gaps.

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