Difference between revisions of "Bioinformatics homework"

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<li><span style="font-size:16px">[[Install and Learn BioPerl]]</span></li>
 
<li><span style="font-size:16px">[[Install and Learn BioPerl]]</span></li>
 
<li><span style="font-size:16px">[[Make a Perl program translating &#39;all&#39; combinations of triple bases into amino acids]]</span></li>
 
<li><span style="font-size:16px">[[Make a Perl program translating &#39;all&#39; combinations of triple bases into amino acids]]</span></li>
 +
<li><span style="font-size:16px">[[Make a Perl program to calculate the lengths of DNA and protein sequences]]</span></li>
 +
<li><span style="font-size:16px">[[Make a Perl program to calculate the length of a Mycoplasma genitalium bacterium]]</span></li>
 
<li><span style="font-size:16px">[[Pick 5 protein sequences and predict their secondary structures using available prediction programs]]</span></li>
 
<li><span style="font-size:16px">[[Pick 5 protein sequences and predict their secondary structures using available prediction programs]]</span></li>
 
<li><span style="font-size:16px">[[Open and re-write one FASTA file containing one protein sequence of TERT]]</span></li>
 
<li><span style="font-size:16px">[[Open and re-write one FASTA file containing one protein sequence of TERT]]</span></li>

Latest revision as of 14:42, 7 May 2018

Jong Bhak's Bioinformatics homework (for any bioinforamtics students)

 

1. Learn Perl programming language and learn bioinformatics using it.

 

 

2. Learn various bioinformatics program and tasks

 

3. Watch the following YouTube lectures;

   MIT 생정보연구자들의 시리즈

   MIT Bioinforamtics intro

   Chris Burge's local alignment lecture from MIT   

   Burge's alignment lecture from MIT

   Genome Assembly from MIT

   David Gifford MIT Library Complexity and Short Read Alignment

   Chip-seq analyses + DNA protein interaction from MIT

    RNA-seq analyses by MIT David Gifford

   Modelling and discovery of sequence motifs by MIT

   Markov and Hidden Markov models for genome and protein sequence features

   RNA-sequence secondary structures by MIT

   Intro to protein structure and comparisons

   Predicting protein structure from MIT

   Predicting protein-protein interactions

   Gene regulartory networks by MIT

   Protein interaction networks by MIT

   Logic modeling of cell signalling networks by MIT

   Analysis of chromatic structure by MIT

   Discoverying quantitative trait loci by MIT

   Human genetics SNPs, GWAS by MIT

   Synthetic biology by MIT

   Causality, Natural language and genome engineering

   George Church's future of genomics and synthetic biology

   Genome Engineering by Jennifer Doudnaby UC Berkeley 제니퍼 다우드나의 강의

 


UNIST Bioinformatics course

생정보학 전반에 대한 온라인 홈페이지