2021

Abdelmageed N , Algergawy A, Samuel S, and König-Ries B: A Data-driven Approach for Core Biodiversity Ontology Development. In S4BIODIV@ICBO, 2021 (Accepted).

Abdelmageed N , Algergawy A, Samuel S, and König-Ries B: BiodivOnto: Towards a Core Ontology for Biodiversity. European Semantic Web Conference, pp. 3-8. Springer, Cham, 2021.

Abdelmageed N , and Schindler S: JenTab: A Toolkit for Semantic Table Annotations. KGC@ESWC, European Semantic Web Conference 2021.

Dittberner A, Ziadat R, Hoffmann F, Pertzborn D, Gassler N, Guntinas-Lichius O.: Fluorescein-Guided Panendoscopy for Head and Neck Cancer Using Handheld Probe-Based Confocal Laser Endomicroscopy: A Pilot Study. Frontiers in Oncology. 2021 Jun 14;11:2186

Giesen J, Kahlmeyer P, Laue S, Mitterreiter M, Nussbaum F, Staudt C & Zarrieß, S. (2021). Method of Moments for Topic Models with Mixed Discrete and Continuous Features. In International Joint Conference on Artificial Intelligence (IJCAI), 2418-2424.

Herrmann KH, Hoffmann F, Ernst G, Pertzborn D, Pelzel D, Geißler K, Guntinas‐Lichius O, Reichenbach JR, von Eggeling F: High‐resolution MRI of the human palatine tonsil and its schematic anatomic 3D reconstruction. Journal of Anatomy. 2021 Aug 3.

Kalvari I, Nawrocki EP, Ontiveros-Palacios N, Argasinska J, Lamkiewicz K, Marz M, Griffiths-Jones S, Toffano-Nioche C, Gautheret D, Weinberg Z, Rivas E, Eddy SR, Finn RD, Bateman A, and Petrov AI, Rfam 14: expanded coverage of metagenomic, viral and microRNA families. 2021

Kerzel D, Samuel S, König-Ries B: Towards Tracking Provenance from Machine Learning Notebooks. 13th International Conference on Knowledge Discovery and Information Retrieval (KDIR), 2021.

Hufsky F, Lamkiewicz K, Almeida A, Aouacheria A, Arighi C, Bateman A, Baumbach J, Beerenwinkel N, Brandt C, Cacciabue M, Chuguransky S, Drechsel O, Finn RD, Fritz A, Fuchs S, Hattab G, Hauschild AC, Heider D, Hoffmann M, Hölzer M, Hoops S, Kaderali L, Kalvari I, von Kleist M, Kmiecinski R, Kühnert D, Lasso G, Libin P, List M, Löchel HF, Martin MJ, Martin R, Matschinske J, McHardy AC, Mendes P, Mistry J, Navratil V, Nawrocki EP, O’Toole ÁN, Ontiveros-Palacios N, Petrov AI, Rangel-Pineros G, Redaschi N, Reimering S, Reinert K, Reyes A, Richardson L, Robertson DL, Sadegh S, Singer JB, Theys K, Upton C, Welzel M, Williams L, Marz M: Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research. Brief Bioinform. 2021 Mar 22;22(2):642-663. doi: 10.1093/bib/bbaa232.PMID: 33147627

Körschens M, Bodesheim P, Römermann C, Bucher SF, Migliavacca M, Ulrich J, Denzler J: Weakly Supervised Segmentation Pretraining for Plant Cover Prediction. In German Conference on Pattern Recognition (GCPR). 2021, September (accepted).

Körschens M, Bodesheim P, Römermann C, Bucher SF, Migliavacca M, Ulrich J, Denzler J: Automatic Plant Cover Estimation with Convolutional Neural Networks. In CS4BIODiversity Workshop at INFORMATIK 2021. 2021, September (accepted).

Lopatina A, Ropele S., Sibgatulin R, Ropele S, Reichenbach JR, Güllmar D: GAN-based analysis for investigation of disease specific image pattern in SWI data of patients suffering from multiple sclerosis. Proceedings of the 2021 ISMRM and SMRT Virtual Conference and Exhibition 15 – 20 May 2021. #1290

Lopatina A, Ropele S., Sibgatulin R, Ropele S, Reichenbach JR, Güllmar D: Relevance analysis of identifying multiple sclerosis patients based on diffusion imaging data using CNN. Proceedings of the 2021 ISMRM and SMRT Virtual Conference and Exhibition 15 – 20 May 2021. #2809

Peter S, Ibrahim B, Dittrich P: Linking network structure and dynamics to describe the set of persistent species in reaction-diffusion systems. SIAM J Appl Dyn Syst 2021, accepted.

Peter S, Dittrich P, Ibrahim B: Structure and hierarchy of SARS-CoV-2 infection dynamics models revealed by reaction network analysis. Viruses 2021, 13(1):14.

Schäfer MB, Zelenka O, Nitz AH, Ohme F, Brügmann B: Training Strategies for Deep Learning Gravitational-Wave Searches. Submitted 6/2021, https://arxiv.org/abs/2106.03741.

Samuel S, Algergawy A, König-Ries B: Towards an Ontology Network for the reproducibility of scientific studies. 8th International Workshop on Ontologies and Conceptual Modeling, co-located with FOIS, 2021.

Samuel S, König-Ries B: ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks. In Provenance and Annotation of Data and Processes – 8th and 9th International Provenance and Annotation Workshop, IPAW 2020 + IPAW 2021, Virtual Event, July 19-22, 2021, Proceedings (Lecture Notes in Computer Science,
Vol. 12839), Boris Glavic, Vanessa Braganholo, and David Koop (Eds.). Springer, 201–206. https://doi.org/10.1007/978-3-030-80960-7_12

Samuel S, Löffler F, König-Ries B: Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles. In Provenance and Annotation of Data and Processes – 8th and 9th International Provenance and Annotation Workshop, IPAW 2020 + IPAW 2021, Virtual Event, July 19-22, 2021, Proceedings (Lecture Notes in Computer Science, Vol. 12839), Boris Glavic, Vanessa Braganholo, and David Koop (Eds.). Springer, 226–230. https://doi.org/10.1007/ 978-3-030-80960-7_17

Shadaydeh M, Müller L, Schneider D, Thümmel M, Kessler T, Denzler J: Analyzing the Direction of Emotional Influence in Nonverbal Dyadic Communication: A Facial-Expression Study. IEEE Access 2021, 9:73780-73790.

Trifunov TV, Shadaydeh M, Barz B, Denzler J: Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning. ICMLA 2021 (accepted).

Trifunov TV, Shadaydeh M, Runge J, Reichstein M, Denzler J: A Data-Driven Approach to Partitioning Net Ecosystem Exchange Using a Deep State Space Model. IEEE Access 2021:9:107873-107883.

Shadaydeh M, Denzler J, García YG, Mahecha M: Time-Frequency Causal Inference Uncovers Anomalous Events in Environmental Systems. In: Fink G., Frintrop S., Jiang X. (eds) Pattern Recognition. DAGM GCPR 2019. Lecture Notes in Computer Science, vol 11824. Springer, Cham.

Ahmad W, Shadaydeh M, Denzler J: Causal inference in nonlinear mutivariate time series using deep network and knockoffs counterfactuals. ICMLA 2021 (accepted).

Voigt H, Meuschke M, Lawonn K, Zarrieß S: Challenges in Designing Natural Language Interfaces for Complex Visual Models. HCINLP. 2021.

2020

Abdelmageed N, Schindler S: JenTab: Matching Tabular Data to Knowledge Graphs. In SemTab@ ISWC, International Conference on Semantic Web, pp. 40-49. 2020.

Abdelmageed N: Towards Transforming Tabular Datasets into Knowledge Graphs. In European Semantic Web Conference (pp. 217-228). Springer, Cham. 2020, May.

Körschens M, Bodesheim P, Römermann C, Bucher SF, Ulrich J, Denzler J: Towards Confirmable Automated Plant Cover Determination. In European Conference on Computer Vision (pp. 312-329). Springer, Cham. 2020, August.

Lopatina A, Ropele S, Reichenbach JR, Güllmar D: Investigation of Deep-Learning-Driven Identification of Multiple Sclerosis Patients Based on Susceptibility-Weighted Images Using Relevance Analysis. Front Neurosci 2020,14:609468.

Lopatina A, Güllmar D, Reichenbach JR: Towards understanding convolutional neural network classification procedure in diagnosing multiple sclerosis. Jahrestagung der Deutschen Gesellschaft für Medizinische Physik – digitaler Kongress, 9-11 September 2020.

Lopatina A, Sibgatulin R, Ropele S, Reichenbach JR, Güllmar D: CNN-based classification of multiple sclerosis using BOLD venographic imaging (SWI) data. Proceedings of the 2020 ISMRM and SMRT Virtual Conference and Exhibition 08-14 August 2020. #1412

Mostajo NF, Lataretu M, Krautwurst S, Mock F, Desirò D, Lamkiewicz K, Collatz M, Schoen A, Weber F, Marz M, Hölzer M: A comprehensive annotation and differential expression analysis of short and long non-coding RNAs in 16 bat genomes. 2020.

Nussbaum F & Giesen J: Pairwise sparse + low-rank models for variables of mixed type. In J. Multivar. Anal. 178:104601. 2020.

Peter S, Ghanim F, Dittrich P, Ibrahim B: Organizations in reaction-diffusion systems: effects of diffusion and boundary conditions. Ecol Compl 2020, 43.

Peter S, Hölzer M, Lamkiewic K, di Fenizio PS, Al Hwaeer H, Marz M, Schuster S, Dittrich P, Ibrahim B: Structure and hierarchy of Influenza virus models revealed by reaction network analysis. Viruses 2019, 11:5.

Samuel S, Shadaydeh M, Böcker S, Brügmann B, Bucher SF, Deckert V, Denzler J, Dittrich P, von Eggeling F, Güllmar D, Guntinas-Lichius O, König-Ries B, Löffler F, Maicher L, Marz M, Migliavacca M, Reichenbach JR, Reichstein M, Römermann C, Wittig A: A virtual “Werkstatt” for digitization in the sciences. Research Ideas and Outcomes 6: e54106. https://doi.org/10.3897/rio.6.e54106

2019

Dukhovny A, Lamkiewicz K, Chen Q, Fricke M, Jabrane-Ferrat N, Marz M, Jung JU, Sklan EH: A CRISPR Activation Screen Identifies Genes That Protect against Zika Virus Infection. J Virol. 2019 Jul 30;93(16):e00211-19. doi: 10.1128/JVI.00211-19. Print 2019 Aug 15. PMID: 31142663

Hoffmann S, Brust CA, Shadaydeh M, Denzler J: Registration of high resolution SAR and optical satellite imagery using fully convolutional networks. IEEE International Geoscience and Remote Sensing Symposium 2019.

Peter S, Hölzer M, Lamkiewicz K, di Fenizio PS, Al Hwaeer H, Marz M, Schuster S, Dittrich P, Ibrahim B: Structure and Hierarchy of Influenza Virus Models Revealed by Reaction Network Analysis. Viruses. 2019 May 16;11(5):449. doi: 10.3390/v11050449. PMID: 31100972

Viehweger A, Krautwurst S, Lamkiewicz K, Madhugiri R, Ziebuhr J, Hölzer M, Marz M: Direct RNA nanopore sequencing of full-length coronavirus genomes provides novel insights into structural variants and enables modification analysis. Genome Res. 2019 Sep;29(9):1545-1554. doi: 10.1101/gr.247064.118. Epub 2019 Aug 22.PMID: 31439691