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Series GSE175942 Query DataSets for GSE175942
Status Public on Jun 02, 2021
Title Quantifying Biopolymer Sequence Recognition using Biophysically Informed Machine Learning
Organisms Drosophila melanogaster; Homo sapiens
Experiment type Other
Summary Quantifying sequence-specific protein-ligand interactions is critical for understanding and exploiting numerous cellular processes, including gene expression regulation and signal transduction. Given their importance, next-generation sequencing (NGS) based assays that characterize such recognition with high-throughput are increasingly being used to profile a range of protein classes and interactions. However, these methods do not measure the biophysical parameters that have long been used to uncover the quantitative rules underlying sequence recognition. We developed a highly flexible machine learning framework, called ProBound, to quantify sequence recognition in terms of biophysical parameters based on NGS data. ProBound quantifies transcription factor (TF) behavior with models that accurately predict binding affinity over a range exceeding that of previous resources, captures the impact of DNA modifications and conformational flexibility of multi-TF complexes, and infers specificity directly from \textit{in vivo} data such as ChIP-seq without peak calling. When coupled with a new assay called Kd-seq, it quantifies the absolute affinity of protein-ligand interactions. Its applicability extends beyond thermodynamic equilibrium binding, to the kinetics of kinase-substrate interactions. Altogether, ProBound provides a versatile algorithmic framework for understanding sequence recognition in a wide variety of biological contexts.
 
Overall design SELEX-seq was performed using the three homeodomain transcription factor Homothorax, Extradenticle and Ultrabithorax (Slattery, Cell, 2011). EpiSELEX-seq, generalize to assay 6mA and 5hMC modified DNA in addition to normal and meCpG, was performed for CEBPg and CEBPg together with ATF4 (Kribelbauer, Cell reports, 2017). K_D-seq was performed for Distal-less. Kinase-substrate sequencing was performed for SRC.
 
Contributor(s) Bussemaker HJ, Mann RS, Shah NH, Rube HT
Citation(s) 35606422
Submission date Jun 01, 2021
Last update date Oct 28, 2022
Contact name Hans Tomas Rube
E-mail(s) [email protected]
Organization name UC Merced
Department Bioengineering
Street address 5200 North Lake Rd.
City Merced
State/province CA
ZIP/Postal code 95343
Country USA
 
Platforms (4)
GPL13304 Illumina HiSeq 2000 (Drosophila melanogaster)
GPL15520 Illumina MiSeq (Homo sapiens)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
Samples (43)
GSM5351572 initialPool.30mer1.R0
GSM5351573 UbxIVa-Hth-Exd.30mer1.R1
GSM5351574 UbxIVa-Hth-Exd.30mer1.R2
Relations
BioProject PRJNA734333
SRA SRP322184

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE175942_200205_Src-Kinase_20m.10000000.tsv.gz 1.0 Mb (ftp)(http) TSV
GSE175942_200205_Src-Kinase_5m.10000000.tsv.gz 1.2 Mb (ftp)(http) TSV
GSE175942_200205_Src-Kinase_60m.10000000.tsv.gz 1.0 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-1.1000000.tsv.gz 2.6 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-10.1000000.tsv.gz 2.5 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-11.1000000.tsv.gz 2.4 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-12.1000000.tsv.gz 2.3 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-2.1000000.tsv.gz 2.4 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-3.1000000.tsv.gz 2.4 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-4.1000000.tsv.gz 2.3 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-5.1000000.tsv.gz 2.6 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-6.1000000.tsv.gz 2.5 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-7.1000000.tsv.gz 2.4 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-8.1000000.tsv.gz 2.3 Mb (ftp)(http) TSV
GSE175942_20201205_DlldN-9.1000000.tsv.gz 2.6 Mb (ftp)(http) TSV
GSE175942_UbxIVa-Hth-Exd.30mer1.100000.tsv.gz 3.4 Mb (ftp)(http) TSV
GSE175942_run_06_05_17_R1_CEBPg_homo_75nM_lowBand_5hmC.100000.tsv.gz 897.2 Kb (ftp)(http) TSV
GSE175942_run_06_05_17_R1_CEBPg_homo_75nM_lowBand_5mCG.100000.tsv.gz 895.5 Kb (ftp)(http) TSV
GSE175942_run_06_05_17_R1_CEBPg_homo_75nM_lowBand_6mA.100000.tsv.gz 902.8 Kb (ftp)(http) TSV
GSE175942_run_06_05_17_R1_CEBPg_homo_75nM_lowBand_None.100000.tsv.gz 897.5 Kb (ftp)(http) TSV
GSE175942_run_10_05_17_R1_ATF4-CEBPg_50nM_highBand_5mCG.100000.tsv.gz 886.7 Kb (ftp)(http) TSV
GSE175942_run_10_05_17_R1_ATF4-CEBPg_50nM_highBand_None.100000.tsv.gz 886.6 Kb (ftp)(http) TSV
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Raw data are available in SRA
Processed data are available on Series record

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