Searching journal content for articles similar to Wetzel et al. 32 (9): 1776.

Displaying results 1-10 of 19

For checked items

view abstracts
download to citation manager

Select this article
Review: Artificial intelligence and machine learning in cell-free-DNA-based diagnostics
- W.H. Adrian Tsui,
- Spencer C. Ding,
- Peiyong Jiang,
- and Y.M. Dennis Lo
Genome Res. January 2025 35: 1-19; doi:10.1101/gr.278413.123
...different tissues. Quadratic programming is an unsupervised learning algorithm that iteratively finds the vertex of a quadratic objective function without the requirement of prior training. In plasma DNA tissue mapping, the proportional contributions from different tissues are estimated in a way...
OPEN ACCESS ARTICLE
Select this article
Method: SelexGLM differentiates androgen and glucocorticoid receptor DNA-binding preference over an extended binding site
- Liyang Zhang,
- Gabriella D. Martini,
- H. Tomas Rube,
- Judith F. Kribelbauer,
- Chaitanya Rastogi,
- Vincent D. FitzPatrick,
- Jon C. Houtman,
- Harmen J. Bussemaker,
- and Miles A. Pufall
Genome Res. January 2018 28: 111-121; Published in Advance December 1, 2017, doi:10.1101/gr.222844.117
...differences in the sets of target genes they control (Maerkl and Quake 2007). To understand gene regulation and regulatory networks, it is therefore essential not only to accurately quantify these differences in DNA recognition but also to determine the structural and physical basis of that specificity...
Select this article
Method: Cross-species analysis of enhancer logic using deep learning
- Liesbeth Minnoye,
- Ibrahim Ihsan Taskiran,
- David Mauduit,
- Maurizio Fazio,
- Linde Van Aerschot,
- Gert Hulselmans,
- Valerie Christiaens,
- Samira Makhzami,
- Monika Seltenhammer,
- Panagiotis Karras,
- Aline Primot,
- Edouard Cadieu,
- Ellen van Rooijen,
- Jean-Christophe Marine,
- Giorgia Egidy,
- Ghanem-Elias Ghanem,
- Leonard Zon,
- Jasper Wouters,
- and Stein Aerts
Genome Res. December 2020 30: 1815-1834; Published in Advance July 30, 2020, doi:10.1101/gr.260844.120
...type, as well as understanding how the specificity of such a network is encoded in the DNA sequence of genomic enhancers. Profiling accessible chromatin via DNase I hypersensitive sequencing (DNase-seq) or via the assay for transposase-accessible chromatin using sequencing (ATAC-seq) represents...
OPEN ACCESS ARTICLE
Select this article
Method: Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks
- David R. Kelley,
- Jasper Snoek,
- and John L. Rinn
Genome Res. July 2016 26: 990-999; Published in Advance May 3, 2016, doi:10.1101/gr.200535.115
...package Basset to apply CNNs to learn the functional activity of DNA sequences from genomics data. We trained Basset on a compendium of accessible genomic sites mapped in 164 cell types by DNase-seq, and demonstrate greater predictive accuracy than previous methods. Basset predictions for the change...
OPEN ACCESS ARTICLE
Select this article
Research: Disclosing the crosstalk among DNA methylation, transcription factors, and histone marks in human pluripotent cells through discovery of DNA methylation motifs
- Phuc-Loi Luu,
- Hans R. Schöler,
- and Marcos J. Araúzo-Bravo
Genome Res. December 2013 23: 2013-2029; Published in Advance October 22, 2013, doi:10.1101/gr.155960.113
...to recruit the ‘‘methylation/ unmethylation machinery’’ to specific loci. The TFs are highpotential recruiting candidates because of their DNA sequence recognition capability. To compare CpGMMs and TFBMs, we designed a technique based on detecting co-occurrences between the targets of the two types of motifs...
Select this article
Review: A systematic guide for identifying transcription factors that directly regulate the expression of a gene of interest
- Andrew D. Bates,
- Dawid Grzela,
- Maciej Studzian,
- Louise Brennan,
- Moli Williams,
- Conor Fawcett,
- Beth Hammond,
- Manreen Grewal,
- Marcin Ratajewski,
- Lukasz Pulaski,
- and Urszula L. McClurg
Genome Res. March 2026 36: 433-459; Published in Advance February 17, 2026, doi:10.1101/gr.281154.125
.... It is critical to appreciate both the biochemistry of TF-DNA binding specificity and the probabilistic nature of tools that predict it. TF binding depends on a number of non-sequence-dependent factors in addition to the local DNA sequence information that prediction tools are based on, leading to an inordinately...
OPEN ACCESS ARTICLE
Select this article
Methods: An ensemble model of competitive multi-factor binding of the genome
- Todd Wasson and
- Alexander J. Hartemink
Genome Res. November 2009 19: 2101-2112; Published in Advance August 31, 2009, doi:10.1101/gr.093450.109
...another for binding sites along the genome. The result is an “occupancy profile,” a probabilistic description of the DNA occupancy of each factor at each position. We implement our model efficiently as the software package COMPETE. We demonstrate genome-wide and at specific loci how modeling nucleosome...
Select this article
Methods: A transcription factor affinity-based code for mammalian transcription initiation
- Molly Megraw,
- Fernando Pereira,
- Shane T. Jensen,
- Uwe Ohler,
- and Artemis G. Hatzigeorgiou
Genome Res. April 2009 19: 644-656; Published in Advance January 13, 2009, doi:10.1101/gr.085449.108
...in genomic scans demonstrates that TSS prediction with both high accuracy and spatial resolution is achievable for a specific but large subgroup of mammalian promoters. The interpretable model structure suggests a DNA code in which canonical sequence features such as TATA-box, Initiator, and GC content do...
Select this article
Method: Anchor: trans-cell type prediction of transcription factor binding sites
- Hongyang Li,
- Daniel Quang,
- and Yuanfang Guan
Genome Res. February 2019 29: 281-292; Published in Advance December 19, 2018, doi:10.1101/gr.237156.118
...be applied to the remaining missing pairs. A major challenge is that TF binding sites are cell-type–specific, which can be attributed to cellular contexts such as chromatin accessibility. Meanwhile, indirect TF-DNA binding and interactions between TFs complicate this regulatory process. Technical issues...
Select this article
Method: Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks
- Daniel Marbach,
- Sushmita Roy,
- Ferhat Ay,
- Patrick E. Meyer,
- Rogerio Candeias,
- Tamer Kahveci,
- Christopher A. Bristow,
- and Manolis Kellis
Genome Res. July 2012 22: 1334-1349; Published in Advance March 28, 2012, doi:10.1101/gr.127191.111
...categorized into physical regulatory networks and functional regulatory networks. A physical regulatory network is one where edges represent a physical interaction between a TF and a target as detected in chromatin immunoprecipitation (ChIP) assays or predicted using sequence-based DNA binding models...

For checked items

view abstracts
download to citation manager

Searching journal content for articles similar to Wetzel et al. 32 (9): 1776.

Search Results

Modify Results

This search

Preprint Server

Current Issue

In This Issue

Citation format:
Results / page:
Results order: