Comprehensive Wet-Bench and Bioinformatics Workflow for Complex Microbiota Using Oxford Nanopore Technologies

Autor: Christoph Ammer-Herrmenau, Nina Pfisterer, Tim van den Berg, Ivana Gavrilova, Ahmad Amanzada, Shiv K. Singh, Alaa Khalil, Rohia Alili, Eugeni Belda, Karine Clement, Ahmed Abd El Wahed, ElSagad Eltayeb Gady, Martin Haubrock, Tim Beißbarth, Volker Ellenrieder, Albrecht Neesse

Publikováno v: mSystems, Vol 6, Iss 4 (2021)

ABSTRACT The advent of high-throughput sequencing techniques has recently provided an astonishing insight into the composition and function of the human microbiome. Next-generation sequencing (NGS) has become the gold standard for advanced microbiome

Externí odkaz: https://doaj.org/article/cd94289276a2419f9d54198f4ccd27cc

NF-Y Binding Site Architecture Defines a C-Fos Targeted Promoter Class.

Autor: Martin Haubrock, Fabian Hartmann, Edgar Wingender

Publikováno v: PLoS ONE, Vol 11, Iss 8, p e0160803 (2016)

ChIP-seq experiments detect the chromatin occupancy of known transcription factors in a genome-wide fashion. The comparisons of several species-specific ChIP-seq libraries done for different transcription factors have revealed a complex combinatorial

Externí odkaz: https://doaj.org/article/72fada5e77ab42b3bf78dc4f1f69d5ee

Effects of the Novel PFKFB3 Inhibitor KAN0438757 on Colorectal Cancer Cells and Its Systemic Toxicity Evaluation In Vivo

Autor: Tiago De Oliveira, Lena-Christin Conradi, Karsten Rauch, Torben Rogge, Tim Beissbarth, Lutz Ackermann, Marcus Edelmann, Kerstin Menck, Sarah-Maria Fendt, Martin Haubrock, Michael Ghadimi, Tina Goldhardt, Mélanie Planque, Nikola Dobrinov Kyuchukov, Shawez Khan, Annalen Bleckmann, Jochen Gaedcke, Hanibal Bohnenberger, Joanna Kalucka

Publikováno v: De Oliveira, T, Goldhardt, T, Edelmann, M, Rogge, T, Rauch, K, Kyuchukov, N D, Menck, K, Bleckman, A, Kalucka, J, Khan, S, Gaedcke, J, Haubrock, M, Beissbarth, T, Bohnenberger, H, Planque, M, Fendt, S M, Ackermann, L, Ghadimi, M & Conradi, L C 2021, ' Effects of the Novel PFKFB3 Inhibitor KAN0438757 on Colorectal Cancer Cells and Its Systemic Toxicity Evaluation In Vivo ', Cancers, vol. 13, no. 5, 1011 . https://doi.org/10.3390/cancers13051011
Cancers
Volume 13
Issue 5
Cancers, Vol 13, Iss 1011, p 1011 (2021)

Simple Summary Glycolysis is one of the hallmarks of cancer. Therefore, the development of novel therapeutical strategies for colorectal cancer targeting glycolysis may improve treatment responses. PFKFB3 expression has been directly associated with

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::514404ff8dae706189a3f056006a4602
https://pure.au.dk/portal/da/publications/effects-of-the-novel-pfkfb3-inhibitor-kan0438757-on-colorectal-cancer-cells-and-its-systemic-toxicity-evaluation-in-vivo(9e40751f-0d4c-4fca-8e16-0ce4b246bddd).html

Impact of mineralocorticoid receptor polymorphisms on urinary electrolyte excretion with and without diuretic drugs

Autor: Martin Haubrock, Jürgen Brockmöller, Mladen V. Tzvetkov, Stefan Viktor Vormfelde, Nawar Dalila, Markus D. Schirmer

Publikováno v: Pharmacogenomics. 16:115-127

Aim: Polymorphisms in the mineralocorticoid receptor may affect urinary sodium and potassium excretion. We investigated polymorphisms in the MR gene in relation to urinary electrolyte excretion in two separate studies. Patients & methods: The genotyp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd6a86ddf2b39b3cb7315e2c6ee885ad
https://doi.org/10.2217/pgs.14.163

PathFinder: reconstruction and dynamic visualization of metabolic pathways

Autor: Martin Haubrock, Robert Giegerich, Jörn Kalinowski, Alexander Goesmann, Folker Meyer

Publikováno v: Scopus-Elsevier

Motivation: Beyond methods for a gene-wise annotation and analysis of sequenced genomes new automated methods for functional analysis on a higher level are needed. The identification of realized metabolic pathways provides valuable information on gen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff1797e3743c0ad6afd7cbdae23de1bb
https://doi.org/10.1093/bioinformatics/18.1.124