Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Developing a ChIP-seq pipeline that analyzes the human genome and its repetitive sequences
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
Place, publisher, year, edition, pages
2017.
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:uu:diva-335914OAI: oai:DiVA.org:uu-335914DiVA, id: diva2:1164159
Educational program
Master Programme in Bioinformatics
Available from: 2017-12-13 Created: 2017-12-10 Last updated: 2017-12-13Bibliographically approved

Open Access in DiVA

fulltext(1622 kB)38 downloads
File information
File name FULLTEXT01.pdfFile size 1622 kBChecksum SHA-512
9e617f5fd0a52776713d3f226d14b1f949be0524641b1e45c3c4c8f81eb33df0d92d989c70303b08642f1a7c65af5d5f0e7a06b81ba2185ea0b31f39448c5a10
Type fulltextMimetype application/pdf

By organisation
Biology Education Centre
Bioinformatics and Systems Biology

Search outside of DiVA

GoogleGoogle Scholar
Total: 38 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 27 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf