Search research articles
Contact Us
Filters
Showing results (31-40 of 50) with videos related to
Page
of 5
Sort By:
Proceedings of the National Academy of Sciences of the United States of America
|
January 18, 2007
The hallmark of AGC kinase functional divergence is its C-terminal tail, a cis-acting regulatory module
Natarajan Kannan, Nina Haste, Susan S Taylor, et al.
Genome Research
|
April 3, 2003
Ran's C-terminal, basic patch, and nucleotide exchange mechanisms in light of a canonical structure for Rab, Rho, Ras, and Ran GTPases
Andrew F Neuwald, Natarajan Kannan, Aleksandar Poleksic, et al.
Plos Computational Biology
|
July 22, 2021
ChIP-GSM: Inferring active transcription factor modules to predict functional regulatory elements
Xi Chen, Andrew F Neuwald, Leena Hilakivi-Clarke, et al.
Database : the Journal of Biological Databases and Curation
|
June 6, 2020
Obtaining extremely large and accurate protein multiple sequence alignments from curated hierarchical alignments
Andrew F Neuwald, Christopher J Lanczycki, Theresa K Hodges, et al.
Scientific Reports
|
September 4, 2021
A Bayesian approach for accurate de novo transcriptome assembly
Xu Shi, Xiao Wang, Andrew F Neuwald, et al.
Cell
|
October 9, 2003
Differential contributions of condensin I and condensin II to mitotic chromosome architecture in vertebrate cells
Takao Ono, Ana Losada, Michiko Hirano, et al.
Scientific Reports
|
October 8, 2020
Author Correction: BICORN: An R package for integrative inference of de novo cis-regulatory modules
Xi Chen, Jinghua Gu, Andrew F Neuwald, et al.
Scientific Reports
|
May 16, 2020
BICORN: An R package for integrative inference of de novo cis-regulatory modules
Xi Chen, Jinghua Gu, Andrew F Neuwald, et al.
Scientific Reports
|
January 12, 2021
Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence
Xi Chen, Jinghua Gu, Andrew F Neuwald, et al.
BMC Bioinformatics
|
April 16, 2021
ChIP-BIT2: a software tool to detect weak binding events using a Bayesian integration approach
Xi Chen, Xu Shi, Andrew F Neuwald, et al.
Page
of 5
Search research articles
Search
Showing results (31-40 of 50) with videos related to
Sort By:
Page
of 5
Proceedings of the National Academy of Sciences of the United States of America
|
January 18, 2007
The hallmark of AGC kinase functional divergence is its C-terminal tail, a cis-acting regulatory module
Natarajan Kannan, Nina Haste, Susan S Taylor, et al.
Genome Research
|
April 3, 2003
Ran's C-terminal, basic patch, and nucleotide exchange mechanisms in light of a canonical structure for Rab, Rho, Ras, and Ran GTPases
Andrew F Neuwald, Natarajan Kannan, Aleksandar Poleksic, et al.
Plos Computational Biology
|
July 22, 2021
ChIP-GSM: Inferring active transcription factor modules to predict functional regulatory elements
Xi Chen, Andrew F Neuwald, Leena Hilakivi-Clarke, et al.
Database : the Journal of Biological Databases and Curation
|
June 6, 2020
Obtaining extremely large and accurate protein multiple sequence alignments from curated hierarchical alignments
Andrew F Neuwald, Christopher J Lanczycki, Theresa K Hodges, et al.
Scientific Reports
|
September 4, 2021
A Bayesian approach for accurate de novo transcriptome assembly
Xu Shi, Xiao Wang, Andrew F Neuwald, et al.
Cell
|
October 9, 2003
Differential contributions of condensin I and condensin II to mitotic chromosome architecture in vertebrate cells
Takao Ono, Ana Losada, Michiko Hirano, et al.
Scientific Reports
|
October 8, 2020
Author Correction: BICORN: An R package for integrative inference of de novo cis-regulatory modules
Xi Chen, Jinghua Gu, Andrew F Neuwald, et al.
Scientific Reports
|
May 16, 2020
BICORN: An R package for integrative inference of de novo cis-regulatory modules
Xi Chen, Jinghua Gu, Andrew F Neuwald, et al.
Scientific Reports
|
January 12, 2021
Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence
Xi Chen, Jinghua Gu, Andrew F Neuwald, et al.
BMC Bioinformatics
|
April 16, 2021
ChIP-BIT2: a software tool to detect weak binding events using a Bayesian integration approach
Xi Chen, Xu Shi, Andrew F Neuwald, et al.
Page
of 5