Anti-NME4 Monoclonal Antibody (DCABH-12587) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use

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Anti-NME4 monoclonal antibody (DCABH-12587) This product is for research use only and is not intended for diagnostic use. PRODUCT INFORMATION Antigen Description The nucleoside diphosphate (NDP) kinases (EC 2.7.4.6) are ubiquitous enzymes that catalyze transfer of gamma-phosphates, via a phosphohistidine intermediate, between nucleoside and dioxynucleoside tri- and diphosphates. The enzymes are products of the nm23 gene family, which includes NME4 (Milon et al., 1997 [PubMed 9099850]). Immunogen A synthetic peptide of human NME4 is used for rabbit immunization. Isotype IgG Source/Host Rabbit Species Reactivity Human Purification Protein A Conjugate Unconjugated Applications Western Blot (Transfected lysate); ELISA Size 1 ea Buffer In 1x PBS, pH 7.4 Preservative None Storage Store at -20°C or lower. Aliquot to avoid repeated freezing and thawing. GENE INFORMATION Gene Name NME4 non-metastatic cells 4, protein expressed in [ Homo sapiens ] Official Symbol NME4 Synonyms NME4; non-metastatic cells 4, protein expressed in; nucleoside diphosphate kinase, mitochondrial; nm23 H4; NM23H4; NDK; NDPKD; NDP kinase D; NDP kinase, mitochondrial; nucleoside diphosphate kinase D; NDPK-D; nm23-H4; Entrez Gene ID 4833 Protein Refseq NP_005000 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 1 © Creative Diagnostics All Rights Reserved UniProt ID A0A087WVT9 Chromosome Location 16p13.3 Pathway Metabolic pathways, organism-specific biosystem; Metabolism, organism-specific biosystem; Metabolism of nucleotides, organism-specific biosystem; Purine metabolism, organism-specific biosystem; Purine metabolism, conserved biosystem; Pyrimidine metabolism, organism-specific biosystem; Pyrimidine metabolism, conserved biosystem. Function ATP binding; kinase activity; metal ion binding; nucleoside diphosphate kinase activity; nucleoside diphosphate kinase activity; nucleotide binding; transferase activity; 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 2 © Creative Diagnostics All Rights Reserved.

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In Silico Prediction of High-Resolution Hi-C Interaction Matrices
ARTICLE https://doi.org/10.1038/s41467-019-13423-8 OPEN In silico prediction of high-resolution Hi-C interaction matrices Shilu Zhang1, Deborah Chasman 1, Sara Knaack1 & Sushmita Roy1,2* The three-dimensional (3D) organization of the genome plays an important role in gene regulation bringing distal sequence elements in 3D proximity to genes hundreds of kilobases away. Hi-C is a powerful genome-wide technique to study 3D genome organization. Owing to 1234567890():,; experimental costs, high resolution Hi-C datasets are limited to a few cell lines. Computa- tional prediction of Hi-C counts can offer a scalable and inexpensive approach to examine 3D genome organization across multiple cellular contexts. Here we present HiC-Reg, an approach to predict contact counts from one-dimensional regulatory signals. HiC-Reg pre- dictions identify topologically associating domains and significant interactions that are enri- ched for CCCTC-binding factor (CTCF) bidirectional motifs and interactions identified from complementary sources. CTCF and chromatin marks, especially repressive and elongation marks, are most important for HiC-Reg’s predictive performance. Taken together, HiC-Reg provides a powerful framework to generate high-resolution profiles of contact counts that can be used to study individual locus level interactions and higher-order organizational units of the genome. 1 Wisconsin Institute for Discovery, 330 North Orchard Street, Madison, WI 53715, USA. 2 Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53715, USA. *email: [email protected] NATURE COMMUNICATIONS | (2019) 10:5449 | https://doi.org/10.1038/s41467-019-13423-8 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-019-13423-8 he three-dimensional (3D) organization of the genome has Results Temerged as an important component of the gene regulation HiC-Reg for predicting contact count using Random Forests.
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