# Week 10 Bioinformatics Database and Resources
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<p align="justify"> Statement before class: All the contents here marked are belong to the course [<font color=orange>Bioinformatics: Introduction and Methods</font>](https://www.coursera.org/learn/bioinformatics-pku/home/welcome). If you like this high-quality course contents, please turn to the official course for more details. Here, i recored the knowledge learnt for convenience. If any copyright problem exist, please tell me, i’ll delete all immediately, Thanks!</p>
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## Overview of Resources
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<font color=orange>`Towards developing a new bioinformatics method:`</font>
- how to identify an important and unsolved biological question
- how to formulate it into a cimputaional problem
- how to come uo with the idea for analgorithm to solve the problem
- how to implement the algorithm
- how to evaluate them
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<font color=orange>`Towards using a new bioinformatics method:`</font>
- what biological questions does it address?
- What are the underlying assumptions?
- What are the different paramates and what do they do?
- What are the accuracies of the method?
- What are its limitations?
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NCBI : National Center for Biotechnology Information ,
EBI: European Bioinformatics Institute,
UCSC Genome Browser,
CBI: European Bioinformatics Institute





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## National Center for Biotechnology Information (NCBI)
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<font color=orange>`Human genes: GeneCards (http://www.genecards.org/)`</font>
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## European Bioinformatics Institute (EBI)
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EBI is a part of European Molecular Biology Laboratory (EMBL)



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**<u>Ensembl</u>**

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**<u>UniProtKB/Swiss-Prot</u>**
IntAct (http://www.ebi.ac.uk/intact/)
Clustal Omega (http://www.clustal.org/omega/)
ClustalW2 - Phylogeny
InterPro & InterProScan
PRIDE (http://www.ebi.ac.uk/pride/)
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## UCSC Genome Browser
UCSC Genome Bioinformatics (http://genome.ucsc.edu/)
The UCSC Genome Bioinformatics has several useful resources. The main part of it is the UCSC Genome Browser. In addition, it is also the portal for the ENCODE project and the Neandertal sequencing project.
whenever you communicate with someone else about genomic coordinates, make sure you specify the version of the assembly you are referring to. The so-called reference genome is not static.

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ENCODE Prohect (http://www.genome.gov/10005107)
Neandetal Genome (http://genome.ucsc.edu/Neandertal/)
UCSC BLAT (http://genome.ucsc.edu/cgi-bin/hgBlat)
UCSC *In-Silico* PCR (http://genome.ucsc.edu/cgi-bin/hgPcr)
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## Individual Resources
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<p align="justify"> SWISS-MODEL is such a prediction web server maintained by the Swiss Institute of Bioinformatics. As I mentioned in Unit 1, there are three main types of methodologies for protein structure prediction. The boundaries between the types are getting blurry as many of the new methods incorporate two or all three of the methodologies. Nevertheless, SWISS-MODEL is based primarily on homology modeling. You can input a protein sequence and SWISS-MODEL searches for homologous proteins with known structure and builds a model for you.</p>

Another structure prediction method with good prediction accuracy is I-TASSER.I-TASSER also uses known protein structures as templates.

QUARK builds ab inito models from putting together small fragments of 1-20 residues long using a knowledge-based force field.

Protein Model Portal that integrates six template-based prediction methods in one user interface.

CASP stands for Critical Assessment of protein Structure Prediction.

Rfam is a database of over 2000 RNA families, including non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Each RNA family is represented by multiple sequence alignments.

SOAPdenovo is a short-read assembly method that can build a de novo draft assembly for large animal and plant genomes from Illumina short reads. It was developed by BGI. The SOAP suite of software also include several other useful tools for next-generation sequencing analysis that you may want to explore.

CNVnator is one of the methods to call structural variations and copy number variations from next-generation sequencing data.

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**<center>Correlated**
<br>
[Bioinformatics/ Introduction and Methos (Week 1 Bioinformatics Introduction)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethosweek1md)
[Bioinformatics/ Introduction and Methos (Week 2 Sequence Alignment)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethosweek2md)
[Bioinformatics/ Introduction and Methos (Week 3 Seq DB and BLAST Algorithnm)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek3md)
[Bioinformatics/ Introduction and Methos (Week 4 Markov Model)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek4md)
[Bioinformatics/ Introduction and Methos (Week 5 From Sequencing to NGS)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek5md)
[Bioinformatics/ Introduction and Methos (Week6 Variant Database)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek6md)
[Bioinformatics/ Introduction and Methos (Week7 Transcriptome Analysis, and RNA-Seq)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek7md)
[Bioinformatics/ Introduction and Methos (Week8 Prediction and Analysis of Noncoding RNA)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek8md)
[Bioinformatics/ Introduction and Methos (Week9 Ontology, Gene Ontology and KEGG Pathway Database)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek9md)
[Bioinformatics/ Introduction and Methos (Week 10 Bioinformatics Database and Resources)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek10md)
[Bioinformatics/ Introduction and Methos (Week 11 New Gene Evolution Detected by Genomic Computation: Basic Concepts and Examples)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek11md)
[Bioinformatics/ Introduction and Methos (Week 12 From Dry to Wet, an Evolutionary Story. Evolution function analysis of DNA methyltransferase)](https://www.haoxi.info/archives/bioinformaticsintroductionandmethodsweek12md)</center>

Bioinformatics: Introduction and Methods (Week 10)