Chapter 3 DoF/6 DoF Localization System for Low Computing Power Mobile Robot Platforms
The combinatorial number of possible methylomes in biological time and space is astronomical. Consequently, the computational analysis of methylomes needs to cater for a variety of data, throughput and resolution. Here, we review recent advances in 2nd generation sequencing (2GS) with a focus on the...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , |
| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
InTechOpen
2015
|
| Subjects: | |
| Online Access: | OAPEN Library: download the publication OAPEN Library: description of the publication |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
MARC
| LEADER | 00000naaaa2200000uu 4500 | ||
|---|---|---|---|
| 001 | oapen_2024_20_500_12657_49130 | ||
| 005 | 20210602 | ||
| 003 | oapen | ||
| 006 | m o d | ||
| 007 | cr|mn|---annan | ||
| 008 | 20210602s2015 xx |||||o ||| 0|eng d | ||
| 020 | |a 61258 | ||
| 040 | |a oapen |c oapen | ||
| 024 | 7 | |a 10.5772/61258 |c doi | |
| 041 | 0 | |a eng | |
| 042 | |a dc | ||
| 072 | 7 | |a MFN |2 bicssc | |
| 100 | 1 | |a Costa, Carlos M. |4 auth | |
| 700 | 1 | |a Sobreira, Héber M. |4 auth | |
| 700 | 1 | |a Sousa, Armando J. |4 auth | |
| 700 | 1 | |a Veiga, Germano |4 auth | |
| 245 | 1 | 0 | |a Chapter 3 DoF/6 DoF Localization System for Low Computing Power Mobile Robot Platforms |
| 260 | |b InTechOpen |c 2015 | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a The combinatorial number of possible methylomes in biological time and space is astronomical. Consequently, the computational analysis of methylomes needs to cater for a variety of data, throughput and resolution. Here, we review recent advances in 2nd generation sequencing (2GS) with a focus on the different methods used for the analysis of MeDIP-seq data. The challenges and opportunities presented by the integration of methylation data with other genomic data types are discussed as is the potential impact of emerging 3rd generation sequencing (3GS) based technologies on methylation analysis. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by/3.0/ |2 cc |4 https://creativecommons.org/licenses/by/3.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Medical genetics |2 bicssc | |
| 653 | |a DNA methylation, methylome, immuno precipitation, analysis pipeline | ||
| 773 | 1 | 0 | |7 nnaa |
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/bitstream/id/406329cb-de49-467f-9205-41de3c3e7103/49181.pdf |7 0 |z OAPEN Library: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/handle/20.500.12657/49130 |7 0 |z OAPEN Library: description of the publication |