Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.
Alexandra M Poos,André Maicher,Anna K. Dieckmann,Marcus Oswald,Roland Eils,Martin Kupiec,Brian Luke,Rainer König,Rainer König +8 more
TL;DR: The results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and the machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.
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Abstract: Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.
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Reprogramming of macrophages employing gene regulatory and metabolic network models
Franziska Hörhold,David Eisel,Marcus Oswald,Amol Kolte,Daniela Röll,Wolfram Osen,Stefan B. Eichmüller,Rainer König +7 more
TL;DR: Gene regulatory network models revealed E2F1, MYC, PPARγ and STAT6 to be the major players in the distinct signatures of these polarization events and represent potential targets for the therapeutic reprogramming of immunosuppressive M2-like macrophages.
The tip and hidden part of the iceberg: Proteinogenic and non-proteinogenic aliphatic amino acids
TL;DR: An overview of natural aliphatic amino acids, up to a side chain length of five carbons, without rings and with an unmodified backbone, and mathematical methods for enumerating the complete list of all potential aliphatics of a given chain length are outlined.
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MiR-192, miR-200c and miR-17 are fibroblast-mediated inhibitors of colorectal cancer invasion.
Volker Ast,Theresa Kordaß,Marcus Oswald,Amol Kolte,David Eisel,Wolfram Osen,Stefan B. Eichmüller,Alexander Berndt,Rainer König +8 more
TL;DR: Expressing these miRNAs singly or in combination in human colon fibroblasts co-cultured with colon cancer cells considerably reduced cancer cell invasion validating these mi RNAs as cancer cell infiltration suppressors in tumor associated fibro Blasts.
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RegulatorTrail: a web service for the identification of key transcriptional regulators.
Tim Kehl,Lara Schneider,Florian Schmidt,Daniel Stöckel,Nico Gerstner,Christina Backes,Eckart Meese,Andreas Keller,Marcel H. Schulz,Hans-Peter Lenhof +9 more
TL;DR: RegulatorTrail is presented, a web service that provides rich functionality for the identification and prioritization of key transcriptional regulators that have a strong impact on natural and pathogenic processes, and successfully identified regulators that might explain the increased malignancy in metastatic melanoma compared to primary tumors, as well as important regulators in macrophages.
PITX1 Is a Regulator of TERT Expression in Prostate Cancer with Prognostic Power
Alexandra M Poos,Cornelia Schroeder,N. Jaishankar,Daniela rer. nat. Röll,Marcus Oswald,Jan Meiners,Delia M. Braun,Caroline Knotz,Lukas Frank,Manuel Gunkel,Roman Spilger,Thomas Wollmann,Adam Polonski,Georgia Makrypidi-Fraune,Christoph Fraune,Markus Graefen,In-Yong Chung,Alexander T. Stenzel,Holger Erfle,Karl C. Rohr,Aria Baniahmad,Guido Sauter,Karsten Rippe,Ronald Simon,Rainer Koenig +24 more
TL;DR: A gene regulatory model based on large data from transcription profiles from prostate cancer and chromatin-immuno-precipitation studies was developed, and the developmental regulator PITX1 regulating telomerase was identified, an excellent prognostic marker for prostate cancer.
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