2024

Hossain, I‡, Fischer, J‡, Burkholz, R*, Quackenbush, J*, Pruning neural network models for gene regulatory dynamics using data and domain knowledge accepted at NeurIPS 2024. (25.8% acceptance rate, Core A*) [preprint]
‡*equal contribution

Fischer, J, Ma, R, Sailing in high-dimensional spaces: Low-dimensional embeddings through angle preservation preprint: arXiv:2406.09876, 2024. [preprint]

Fischer, J, Shutta, KH, Chen, C, Fanfani, V, Saha, E, Mandros, P, Guebila, MB, Xiu, J, Nieva, J, Liu, S, Uprety, D, Spetzler, D, Lopes-Ramos, CM, DeMeo, D, Quackenbush, J, Selective loss of Y chromosomes in lung adenocarcinoma modulates the tumor immune environment through cancer/testis antigens bioRxiv:10.1101/2024.09.19.613876v1, 2024. [preprint]

Lin, Y, Breuer, K, Weichenhan, D, Lafrenz, P, Wilk, A, Chepeleva, M, Mücke, O, Schönung, M, Petermann, F, Kensche, P, Weiser, L, Thommen, F, Giacomelli, G, Nordstroem, K, Gonzales-Avalos, E, Merkel, A, Kretzmer, H, Fischer, J, Krämer, S, Iskar, M, Wolf, S, Buchhalter, I, Esteller, M, Lawerenz, C, Twardziok, S, Zapatka, M, Hovestadt, V, Schlesner, M, Schulz, M, Hoffmann, S, Gerhauser, C, Walter, J, Hartmann, M, Lipka, DB, Assenov, Y, Bock, C, Plass, C, Toth, R, Lutsik, P Pipeline Olympics: continuable benchmarking of computational workflows for DNA methylation sequencing data against an experimental gold-standard bioRxiv:10.1101/2024.09.16.609142, 2024. [preprint]

Mandros, P, Gallagher, I, Fanfani, V, Chen, C, Fischer, J, Ismail, A, Hsu, L, Saha, E, DeConti, DK, Quackenbush, J, node2vec2rank: Large Scale and Stable Graph Differential Analysis via Multi-Layer Node Embeddings and Ranking preprint: bioRxiv:10.1101/2024.06.16.599201v1, 2024. [preprint]

Walter, NP, Fischer, J, Vreeken, J, Finding Interpretable Class-Specific Patterns through Efficient Neural Search AAAI Conference on Artificial Intelligence (AAAI), 2024. (23.8% acceptance rate, Core A*) [Article]

Saha, E‡, Fanfani, V‡, Mandros, P, Guebila, MB, Fischer, J, Shutta, KH, Glass, K, DeMeo, DL, Lopes-Ramos, CM, Quackenbush, J, Bayesian inference of sample-specific coexpression networks Genome Research, CSHL, 2024. (IF: 6.70, 2022) [PDF]
‡equal contribution

Saha, E‡, Fanfani, V‡, Mandros, P, Guebila, MB, Fischer, J, Shutta, KH, Glass, K, DeMeo, DL, Lopes-Ramos, CM, Quackenbush, J, Bayesian Optimized sample-specific Networks Obtained By Omics data (BONOBO) Conference for Research in Computational Molecular Biology (RECOMB), 2024. (16.5% acceptance rate) [Conference paper]
‡equal contribution

Saha, E, Guebila, MB, Fanfani, V, Fischer, J, Shutta, KH, Mandros, P, DeMeo, DL, Quackenbush, J, Lopes-Ramos, CM, Gene regulatory Networks Reveal Sex Difference in Lung Adenocarcinoma Biology of Sex Differences 15(62), 2024. (IF: 8.24, 2022) [preprint] [Article]

Hossain, I, Fanfani, V, Fischer, J, Quackenbush, J, Burkholz, J, Biologically informed NeuralODEs for genome-wide regulatory dynamics Genome Biology 25(127), BMC, 2024. (IF: 17.4, 2022) [Article]

2023

Hedderich, M‡, Fischer, J‡, Klakow, D, Vreeken, J, Understanding and Mitigating Classification Errors Through Interpretable Token Patterns Empirical Methods in Natural Language Processing (EMNLP) BlackboxNLP workshop, 2023. [preprint]
‡equal contribution

Kamp, M, Fischer, J, Vreeken, J, Federated Learning from Small Datasets. International Conference on Learning Representations (ICLR), OpenReview, 2023. (31.8% acceptance rate, Core A*) [PDF]

Fischer, J, Burkholz, R, Vreeken, J, Preserving local densities in low-dimensional embeddings. preprint: arXiv:2301.13732, 2023. [preprint]

Fischer, J, Schulz, MH, Efficiently Quantifying DNA Methylation for Bulk- and Single-cell Bisulfite Data. Bioinformatics 39(6), Oxford University Press, 2023. (IF: 5.8, 2023) [Article]

2022

Hedderich, M‡, Fischer, J‡, Klakow, D, Vreeken, J, Label-Descriptive Patterns and their Application to Characterizing Classification Errors. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2022. (21.9% acceptance rate, Core A*) [PDF]
‡equal contribution

Fischer, J, Burkholz, R, Plant ‘n’ Seek: Can You Find the Winning Ticket? International Conference on Learning Representations (ICLR), OpenReview, 2022. (32.9% acceptance rate, Core A*) [PDF]

Marx, A, Fischer, J, Estimating Mutual Information via Geodesic kNN. SIAM Conference on Data Mining (SDM), SIAM, 2022. (27.9% acceptance rate, Core A) [Article]

2021

Fischer, J, Vreeken, J, Differentiable Pattern Set Mining. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2021. (15.4% acceptance rate, Core A*) [Article]

Fischer, J, Oláh, A, Vreeken, J, What’s in the Box? Explaining Neural Networks with Robust Rules. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2021. (21.4% acceptance rate, Core A*) [PDF]

Fischer, J, Ardakani, FB, Kattler, K, Walter, J, Schulz, MH, CpG content-dependent associations between transcription factors and histone modifications. Plos ONE 16(4): e0249985, 2021. (IF: 3.7, 2023) [Article]

Fischer, J‡, Gadhikar‡, A, Burkholz, R, Lottery Tickets with Nonzero Biases. preprint: arXiv:2110.11150, 2021. [preprint]
‡equal contribution

Heiter, E, Fischer, J, Vreeken, J, Factoring out prior knowledge from low-dimensional embeddings. preprint: arXiv:2103.01828, 2021. [preprint]

2020

Fischer, J, Vreeken, J, Discovering Succinct Pattern Sets Expressing Co-Occurrence and Mutual Exclusivity. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2020. (16.8% acceptance rate, Core A*) [Article]

2019

Fischer, J, Vreeken, J, Sets of Robust Rules, and How to Find Them In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Data (ECMLPKDD), Springer, 2019. (17.7% acceptance rate, Core A, ==selected plenary talk==, <5% of accepted papers) [Article]

Fischer, J, Schulz, MH, Fast and accurate bisulfite alignment and methylation calling for mammalian genomes. Talk at ISMB/ECCB, Basel, Switzerland, 2019.

2018

Ardakani, FB Kattler, K, Nordström, KJ, Gasparoni, N, Gasparoni, G, Fuchs, S, Sinha, A, Barann, M, Ebert, P, Fischer, J, Hutter, B, Zipprich, G, Imbusch, CD, Felder, B, Eils, J, Brors, B, Lengauer, T, Manke, T, Rosenstiel, P, Walter, J, Schulz, MH, Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters. Epigenetics & Chromatin 11(1): 66, 2018. (IF: 5.5, 2023) [Article]

Fischer, J, Schulz, MH, Fast and accurate bisulfite alignment and methylation calling for mammalian genomes. Short talk/poster at RECOMB-seq/RECOMB, Paris, France, 2018.

Theses

Fischer, J, More than the sum of its parts – pattern mining, neural networks, and how they complement each other. Doctoral Dissertation, 2022. [PDF]

Fischer, J, Fast and accurate bisulfite alignment and methylation calling for mammalian genomes. Master thesis, 2017.

Fischer, J, Inferring associations between transcription factors and histone modifications using a fused lasso approach. Bachelor thesis, 2015.