TY  - JOUR
A1  - Merget, Benjamin
A1  - Koetschan, Christian
A1  - Hackl, Thomas
A1  - Förster, Frank
A1  - Dandekar, Thomas
A1  - Müller, Tobias
A1  - Schultz, Jörg
A1  - Wolf, Matthias
T1  - The ITS2 Database
JF  - Journal of Visual Expression
N2  - The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation.

The ITS2 Database presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank accurately reannotated. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold.

The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE and ProfDistS for multiple sequence-structure alignment calculation and Neighbor Joining tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure.

In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.
KW  - homology modeling
KW  - molecular systematics
KW  - internal transcribed spacer 2
KW  - alignment
KW  - genetics
KW  - secondary structure
KW  - ribosomal RNA
KW  - phylogenetic tree
KW  - phylogeny
Y1  - 2012
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-124600
VL  - 61
IS  - e3806
ER  - 
TY  - JOUR
A1  - Pawellek, Ruben
A1  - Krmar, Jovana
A1  - Leistner, Adrian
A1  - Djajić, Nevena
A1  - Otašević, Biljana
A1  - Protić, Ana
A1  - Holzgrabe, Ulrike
T1  - Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach
JF  - Journal of Cheminformatics
N2  - The charged aerosol detector (CAD) is the latest representative of aerosol-based detectors that generate a response independent of the analytes' chemical structure. This study was aimed at accurately predicting the CAD response of homologous fatty acids under varying experimental conditions. Fatty acids from C12 to C18 were used as model substances due to semivolatile characterics that caused non-uniform CAD behaviour. Considering both experimental conditions and molecular descriptors, a mixed quantitative structure-property relationship (QSPR) modeling was performed using Gradient Boosted Trees (GBT). The ensemble of 10 decisions trees (learning rate set at 0.55, the maximal depth set at 5, and the sample rate set at 1.0) was able to explain approximately 99% (Q\(^2\): 0.987, RMSE: 0.051) of the observed variance in CAD responses. Validation using an external test compound confirmed the high predictive ability of the model established (R-2: 0.990, RMSEP: 0.050). With respect to the intrinsic attribute selection strategy, GBT used almost all independent variables during model building. Finally, it attributed the highest importance to the power function value, the flow rate of the mobile phase, evaporation temperature, the content of the organic solvent in the mobile phase and the molecular descriptors such as molecular weight (MW), Radial Distribution Function-080/weighted by mass (RDF080m) and average coefficient of the last eigenvector from distance/detour matrix (Ve2_D/Dt). The identification of the factors most relevant to the CAD responsiveness has contributed to a better understanding of the underlying mechanisms of signal generation. An increased CAD response that was obtained for acetone as organic modifier demonstrated its potential to replace the more expensive and environmentally harmful acetonitrile.
KW  - High-performance liquid chromatography (HPLC)
KW  - Charged aerosol detector (CAD)
KW  - Gradient boosted trees (GBT)
KW  - Quantitative structure-property relationship modeling (QSPR)
KW  - Fatty acids
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-261618
VL  - 13
IS  - 1
ER  -