Importing statistical measures into Artemis enhances gene identification in the Leishmania genome project.
Importing statistical measures into Artemis enhances gene identification in the Leishmania genome project.
复制标题
将统计测量数据导入 Artemis 可以增强利什曼原虫基因组计划中的基因识别。
DOI:
10.1186/1471-2105-4-23
复制
发表时间:
2003-06-07
影响因子:
3
通讯作者:
Myler PJ
中科院分区:
文献类型:
--
作者:
Aggarwal G;Worthey EA;McDonagh PD;Myler PJ
Seattle Biomedical Research Institute (SBRI) as part of the Leishmania Genome Network (LGN) is sequencing chromosomes of the trypanosomatid protozoan species Leishmania major. At SBRI, chromosomal sequence is annotated using a combination of trained and untrained non-consensus gene-prediction algorithms with ARTEMIS, an annotation platform with rich and user-friendly interfaces. Here we describe a methodology used to import results from three different protein-coding gene-prediction algorithms (GLIMMER, TESTCODE and GENESCAN) into the ARTEMIS sequence viewer and annotation tool. Comparison of these methods, along with the CODONUSAGE algorithm built into ARTEMIS, shows the importance of combining methods to more accurately annotate the L. major genomic sequence. An improvised and powerful tool for gene prediction has been developed by importing data from widely-used algorithms into an existing annotation platform. This approach is especially fruitful in the Leishmania genome project where there is large proportion of novel genes requiring manual annotation.
登录
查看更多内容
影响因子:
14.9
作者:
STADEN, R;MCLACHLAN, AD
通讯作者:
MCLACHLAN, AD
影响因子:
7
作者:
Howe, KL;Chothia, T;Durbin, R
通讯作者:
Durbin, R
影响因子:
3.5
作者:
Claverie, JM
通讯作者:
Claverie, JM
DOI:
10.1073/pnas.96.6.2902
发表时间:
1999-03-16
影响因子:
11.1
作者:
Myler, PJ;Audleman, L;Stuart, K
通讯作者:
Stuart, K
影响因子:
14.9
作者:
Delcher, AL;Harmon, D;Salzberg, SL
通讯作者:
Salzberg, SL