TY - JOUR A1 - Aydinli, Muharrem A1 - Liang, Chunguang A1 - Dandekar, Thomas T1 - Motif and conserved module analysis in DNA (promoters, enhancers) and RNA (lncRNA, mRNA) using AlModules JF - Scientific Reports N2 - Nucleic acid motifs consist of conserved and variable nucleotide regions. For functional action, several motifs are combined to modules. The tool AIModules allows identification of such motifs including combinations of them and conservation in several nucleic acid stretches. AIModules recognizes conserved motifs and combinations of motifs (modules) allowing a number of interesting biological applications such as analysis of promoter and transcription factor binding sites (TFBS), identification of conserved modules shared between several gene families, e.g. promoter regions, but also analysis of shared and conserved other DNA motifs such as enhancers and silencers, in mRNA (motifs or regulatory elements e.g. for polyadenylation) and lncRNAs. The tool AIModules presented here is an integrated solution for motif analysis, offered as a Web service as well as downloadable software. Several nucleotide sequences are queried for TFBSs using predefined matrices from the JASPAR DB or by using one’s own matrices for diverse types of DNA or RNA motif discovery. Furthermore, AIModules can find TFBSs common to two or more sequences. Demanding high or low conservation, AIModules outperforms other solutions in speed and finds more modules (specific combinations of TFBS) than alternative available software. The application also searches RNA motifs such as polyadenylation site or RNA–protein binding motifs as well as DNA motifs such as enhancers as well as user-specified motif combinations (https://bioinfo-wuerz.de/aimodules/; alternative entry pages: https://aimodules.heinzelab.de or https://www.biozentrum.uni-wuerzburg.de/bioinfo/computing/aimodules). The application is free and open source whether used online, on-site, or locally. KW - AIModules KW - nucleic acid motifs KW - DNA Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-301268 VL - 12 IS - 1 ER - TY - JOUR A1 - Peindl, Matthias A1 - Göttlich, Claudia A1 - Crouch, Samantha A1 - Hoff, Niklas A1 - Lüttgens, Tamara A1 - Schmitt, Franziska A1 - Pereira, Jesús Guillermo Nieves A1 - May, Celina A1 - Schliermann, Anna A1 - Kronenthaler, Corinna A1 - Cheufou, Danjouma A1 - Reu-Hofer, Simone A1 - Rosenwald, Andreas A1 - Weigl, Elena A1 - Walles, Thorsten A1 - Schüler, Julia A1 - Dandekar, Thomas A1 - Nietzer, Sarah A1 - Dandekar, Gudrun T1 - EMT, stemness, and drug resistance in biological context: a 3D tumor tissue/in silico platform for analysis of combinatorial treatment in NSCLC with aggressive KRAS-biomarker signatures JF - Cancers N2 - Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRAS\(^{G12C}\) or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-β. To investigate further determinants of drug response, we tested several drugs in combination with a KRAS\(^{G12C}\) inhibitor in KRAS\(^{G12C}\) mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures. KW - EMT KW - drug resistance KW - invasion KW - stemness KW - 3D lung tumor tissue models KW - KRAS biomarker signatures KW - boolean in silico models KW - targeted combination therapy Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-270744 SN - 2072-6694 VL - 14 IS - 9 ER - TY - INPR A1 - Dandekar, Thomas T1 - Qubit transition into defined Bits: A fresh perspective for cosmology and unifying theories N2 - In this view point we do not change cosmology after the hot fireball starts (hence agrees well with observation), but the changed start suggested and resulting later implications lead to an even better fit with current observations (voids, supercluster and galaxy formation; matter and no antimatter) than the standard model with big bang and inflation: In an eternal ocean of qubits, a cluster of qubits crystallizes to defined bits. The universe does not jump into existence (“big bang”) but rather you have an eternal ocean of qubits in free super-position of all their quantum states (of any dimension, force field and particle type) as permanent basis. The undefined, boiling vacuum is the real “outside”, once you leave our everyday universe. A set of n Qubits in the ocean are “liquid”, in very undefined state, they have all their m possibilities for quantum states in free superposition. However, under certain conditions the qubits interact, become defined, and freeze out, crystals form and give rise to a defined, real world with all possible time series and world lines. GR holds only within the crystal. In our universe all n**m quantum possibilities are nicely separated and crystallized out to defined bit states: A toy example with 6 qubits each having 2 states illustrates, this is completely sufficient to encode space using 3 bits for x,y and z, 1 bit for particle type and 2 bits for its state. Just by crystallization, space, particles and their properties emerge from the ocean of qubits, and following the arrow of entropy, time emerges, following an arrow of time and expansion from one corner of the toy universe to everywhere else. This perspective provides time as emergent feature considering entropy: crystallization of each world line leads to defined world lines over their whole existence, while entropy ensures direction of time and higher representation of high entropy states considering the whole crystal and all slices of world lines. The crystal perspective is also economic compared to the Everett-type multiverse, each qubit has its m quantum states and n qubits interacting forming a crystal and hence turning into defined bit states has only n**m states and not more states. There is no Everett-type world splitting with every decision but rather individual world trajectories reside in individual world layers of the crystal. Finally, bit-separated crystals come and go in the qubit ocean, selecting for the ability to lay seeds for new crystals. This self-organizing reproduction selects over generations also for life-friendliness. Mathematical treatment introduces quantum action theory as a framework for a general lattice field theory extending quantum chromo dynamics where scalar fields for color interaction and gravity have to be derived from the permeating qubit-interaction field. Vacuum energy should get appropriately low by the binding properties of the qubit crystal. Connections to loop quantum gravity, string theory and emergent gravity are discussed. Standard physics (quantum computing; crystallization, solid state physics) allow validation tests of this perspective and will extend current results. KW - qubit KW - cosmology KW - phase transition KW - unified theories KW - crystallization KW - emergent gravity Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-266418 ER -