@article {70155, title = {Sexual dimorphism in the complete connectome of the Drosophila male central nervous system}, journal = {bioRxiv}, year = {2025}, month = {2025 Oct 09}, abstract = {

Sex differences in behaviour exist across the animal kingdom, typically under strong genetic regulation. In Drosophila, previous work has shown that fruitless and doublesex transcription factors identify neurons driving sexually dimorphic behaviour. However, the organisation of dimorphic neurons into functional circuits remains unclear.We now present the connectome of the entire Drosophila male central nervous system. This contains 166,691 neurons spanning the brain and ventral nerve cord, fully proofread and comprehensively annotated including fruitless and doublesex expression and 11,691 cell types. By comparison with a previous female brain connectome, we provide the first comprehensive description of the differences between male and female brains to synaptic resolution. Of 7,319 cross-matched cell types in the central brain, 114 are dimorphic with an additional 262 male- and 69 female-specific (totalling 4.8\% of neurons in males and 2.4\% in females).This resource enables analysis of full sensory-to-motor circuits underlying complex behaviours as well as the impact of dimorphic elements. Sex-specific and dimorphic neurons are concentrated in higher brain centres while the sensory and motor periphery are largely isomorphic. Within higher centres, male-specific connections are organised into hotspots defined by male-specific neurons or the presence of male-specific arbours on neurons that are otherwise similar between sexes. Numerous circuit switches reroute sensory information to form conserved, antagonistic circuits controlling opposing behaviours.

}, doi = {10.1101/2025.10.09.680999}, url = {https://www.biorxiv.org/content/early/2025/10/09/2025.10.09.680999}, author = {Berg, Stuart and Beckett, Isabella R and Costa, Marta and Schlegel, Philipp and Januszewski, Micha{\l} and Marin, Elizabeth C and Nern, Aljoscha and Preibisch, Stephan and Qiu, Wei and Takemura, Shin-ya and Fragniere, Alexandra MC and Champion, Andrew S and Adjavon, Diane-Yayra and Cook, Michael and Gkantia, Marina and Hayworth, Kenneth J and Huang, Gary B and Katz, William T and K{\"a}mpf, Florian and Lu, Zhiyuan and Ordish, Christopher and Paterson, Tyler and St{\"u}rner, Tomke and Trautman, Eric T and Whittle, Catherine R and Burnett, Laura E and Hoeller, Judith and Li, Feng and Loesche, Frank and Morris, Billy J and Pietzsch, Tobias and Pleijzier, Markus W and Silva, Valeria and Yin, Yijie and Ali, Iris and Badalamente, Griffin and Bates, Alexander Shakeel and Bogovic, John and Brooks, Paul and Cachero, Sebastian and Canino, Brandon S and Chaisrisawatsuk, Bhumpanya and Clements, Jody and Crowe, Arthur and de Haan Vicente, In{\^e}s and Dempsey, Georgia and Don{\`a}, Erika and dos Santos, M{\'a}rcia and Dreher, Marisa and Dunne, Christopher R and Eichler, Katharina and Finley-May, Samantha and Flynn, Miriam A and Hameed, Imran and Hopkins, Gary Patrick and Hubbard, Philip M and Kiassat, Ladann and Kovalyak, Julie and Lauchie, Shirley A and Leonard, Meghan and Lohff, Alanna and Longden, Kit D and Maldonado, Charli A and Mitletton, Myrto and Moitra, Ilina and Moon, Sung Soo and Mooney, Caroline and Munnelly, Eva J and Okeoma, Nneoma and Olbris, Donald J and Pai, Anika and Patel, Birava and Phillips, Emily M and Plaza, Stephen M and Richards, Alana and Rivas Salinas, Jennifer and Roberts, Ruair{\'\i} Jv and Rogers, Edward M and Scott, Ashley L and Scuderi, Louis A and Seenivasan, Pavithraa and Serratosa Capdevila, Laia and Smith, Claire and Svirskas, Rob and Takemura, Satoko and Tastekin, Ibrahim and Thomson, Alexander and Umayam, Lowell and Walsh, John J and Whittome, Holly and Xu, C Shan and Yakal, Emily A and Yang, Tansy and Zhao, Arthur and George, Reed and Jain, Viren and Jayaraman, Vivek and Korff, Wyatt and Meissner, Geoffrey W and Romani, Sandro and Funke, Jan and Knecht, Christopher and Saalfeld, Stephan and Scheffer, Louis K and Waddell, Scott and Card, Gwyneth M and Ribeiro, Carlos and Reiser, Michael B and Hess, Harald F and Rubin, Gerald M and Jefferis, Gregory Sxe} } @article {48647, title = {The candidate multi-cut for cell segmentation.}, journal = {2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)}, year = {2017}, month = {2017 Jul 04}, abstract = {

Two successful approaches for the segmentation of biomedical images are (1) the selection of segment candidates from a merge-tree, and (2) the clustering of small superpixels by solving a Multi-Cut problem. In this paper, we introduce a model that unifies both approaches. Our model, the Candidate Multi-Cut (CMC), allows joint selection and clustering of segment candidates from a merge-tree. This way, we overcome the respective limitations of the individual methods: (1) the space of possible segmentations is not constrained to candidates of a merge-tree, and (2) the decision for clustering can be made on candidates larger than superpixels, using features over larger contexts. We solve the optimization problem of selecting and clustering of candidates using an integer linear program. On datasets of 2D light microscopy of cell populations and 3D electron microscopy of neurons, we show that our method generalizes well and generates more accurate segmentations than merge-tree or Multi-Cut methods alone.

}, doi = {10.1109/ISBI.2018.8363658}, author = {Funke, Jan and Zhang, Chong and Pietzsch, Tobias and Gonzalez Ballester, Miguel A and Saalfeld, Stephan} } @article {48278, title = {Multi-view light-sheet imaging and tracking with the MaMuT software reveals the cell lineage of a direct developing arthropod limb.}, journal = {eLife}, volume = {7}, year = {2017}, month = {2018 Mar 29}, pages = {e34410}, abstract = {

During development, coordinated cell behaviors orchestrate tissue and organ morphogenesis. Detailed descriptions of cell lineages and behaviors provide a powerful framework to elucidate the mechanisms of morphogenesis. To study the cellular basis of limb development, we imaged transgenic fluorescently-labeled embryos from the crustacean Parhyale hawaiensis with multi-view light-sheet microscopy at high spatiotemporal resolution over several days of embryogenesis. The cell lineage of outgrowing thoracic limbs was reconstructed at single-cell resolution with new software called Massive Multi-view Tracker (MaMuT). In silico clonal analyses suggested that the early limb primordium becomes subdivided into anterior-posterior and dorsal-ventral compartments whose boundaries intersect at the distal tip of the growing limb. Limb-bud formation is associated with spatial modulation of cell proliferation, while limb elongation is also driven by preferential orientation of cell divisions along the proximal-distal growth axis. Cellular reconstructions were predictive of the expression patterns of limb development genes including the BMP morphogen Decapentaplegic.

}, doi = {10.7554/eLife.34410}, author = {Wolff, Carsten and Tinevez, Jean-Yves and Pietzsch, Tobias and Stamataki, Evangelia and Harich, Benjamin and Guignard, Leo and Preibisch, Stephan and Shorte, Spencer and Keller, Philipp J and Tomancak, Pavel and Pavlopoulos, Anastasios} } @article {46817, title = {BigDataViewer: visualization and processing for large image data sets.}, journal = {Nature Methods}, volume = {12}, year = {2015}, month = {2015 May 28}, pages = {481-3}, issn = {1548-7105}, doi = {10.1038/nmeth.3392}, author = {Pietzsch, Tobias and Saalfeld, Stephan and Preibisch, Stephan and Tomancak, Pavel} } @article {45049, title = {Bioimage informatics in the context of Drosophila research.}, journal = {Methods}, volume = {68}, year = {2014}, month = {2014 Jun 15}, pages = {60-73}, abstract = {

Modern biological research relies heavily on microscopic imaging. The advanced genetic toolkit of Drosophila makes it possible to label molecular and cellular components with unprecedented level of specificity necessitating the application of the most sophisticated imaging technologies. Imaging in Drosophila spans all scales from single molecules to the entire populations of adult organisms, from electron microscopy to live imaging of developmental processes. As the imaging approaches become more complex and ambitious, there is an increasing need for quantitative, computer-mediated image processing and analysis to make sense of the imagery. Bioimage Informatics is an emerging research field that covers all aspects of biological image analysis from data handling, through processing, to quantitative measurements, analysis and data presentation. Some of the most advanced, large scale projects, combining cutting edge imaging with complex bioimage informatics pipelines, are realized in the Drosophila research community. In this review, we discuss the current research in biological image analysis specifically relevant to the type of systems level image datasets that are uniquely available for the Drosophila model system. We focus on how state-of-the-art computer vision algorithms are impacting the ability of Drosophila researchers to analyze biological systems in space and time. We pay particular attention to how these algorithmic advances from computer science are made usable to practicing biologists through open source platforms and how biologists can themselves participate in their further development.

}, issn = {1095-9130}, doi = {10.1016/j.ymeth.2014.04.004}, author = {Jug, Florian and Pietzsch, Tobias and Preibisch, Stephan and Tomancak, Pavel} } @proceedings {46790, title = {Advanced Programming with ImgLib2}, year = {2012}, month = {2012 Oct 24}, address = {Mondorf-les-Bains, Luxembourg}, author = {Pietzsch, Tobias and Preibisch, Stephan and Tomancak, Pavel and Saalfeld, Stephan} } @article {5634, title = {Fiji: an open-source platform for biological-image analysis.}, journal = {Nature Methods}, volume = {9}, year = {2012}, month = {2012 Jul}, pages = {676-82}, abstract = {

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

}, keywords = {Algorithms, Animals, Brain, Computational Biology, Computer-Assisted, Drosophila melanogaster, Image Enhancement, Image Processing, Imaging, Information Dissemination, Software, Software Design, Three-Dimensional}, issn = {1548-7105}, doi = {10.1038/nmeth.2019}, author = {Schindelin, Johannes and Arganda-Carreras, Ignacio and Frise, Erwin and Kaynig, Verena and Longair, Mark and Pietzsch, Tobias and Preibisch, Stephan and Rueden, Curtis and Saalfeld, Stephan and Schmid, Benjamin and Tinevez, Jean-Yves and White, Daniel James and Hartenstein, Volker and Eliceiri, Kevin and Tomancak, Pavel and Cardona, Albert} } @article {46160, title = {ImgLib2--generic image processing in Java.}, journal = {Bioinformatics}, volume = {28}, year = {2012}, month = {2012 Nov 15}, pages = {3009-11}, abstract = {

SUMMARY: ImgLib2 is an open-source Java library for n-dimensional data representation and manipulation with focus on image processing. It aims at minimizing code duplication by cleanly separating pixel-algebra, data access and data representation in memory. Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation. ImgLib2 illustrates that an elegant high-level programming interface can be achieved without sacrificing performance. It provides efficient implementations of common data types, storage layouts and algorithms. It is the data model underlying ImageJ2, the KNIME Image Processing toolbox and an increasing number of Fiji-Plugins.

AVAILABILITY: ImgLib2 is licensed under BSD. Documentation and source code are available at http://imglib2.net and in a public repository at https://github.com/imagej/imglib.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Online.

CONTACT: saalfeld@mpi-cbg.de

}, keywords = {Algorithms, Image Processing, Computer-Assisted, Programming Languages, Software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/bts543}, author = {Pietzsch, Tobias and Preibisch, Stephan and Tomancak, Pavel and Saalfeld, Stephan} } @proceedings {46789, title = {ImgLib2{\textemdash}Generic Image Processing in Java}, year = {2012}, month = {2012 Oct 24}, address = {Mondorf-les-Bains, Luxembourg}, author = {Saalfeld, Stephan and Pietzsch, Tobias and Tomancak, Pavel and Preibisch, Stephan} } @proceedings {46791, title = {Introduction to ImgLib2}, year = {2012}, month = {2012 Oct 24}, address = {Mondorf-les-Bains, Luxembourg}, author = {Preibisch, Stephan and Pietzsch, Tobias and Myers, Eugene and Tomancak, Pavel and Saalfeld, Stephan} }