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This folder holds the following references to publications, sorted by year and author.

There are 9 references in this bibliography folder.

Elsner, J, Mensah, MA, Holtgrewe, M, Hertzberg, J, Bigoni, S, Busche, A, Coutelier, M, de Silva, DC, Elçioglu, N, Filges, I, Gerkes, E, Girisha, KM, Graul-Neumann, L, Jamsheer, A, Krawitz, P, Kurth, I, Markus, S, Megarbane, A, Reis, A, Reuter, MS, Svoboda, D, Teller, C, Tuysuz, B, Türkmen, S, Wilson, M, Woitschach, R, Vater, I, Caliebe, A, Hülsemann, W, Horn, D, Mundlos, S, and Spielmann, M (2021).
Genome sequencing in families with congenital limb malformations
Human Genetics, 140(8):1229--1239.

Glessner, JT, Hou, X, Zhong, C, Zhang, J, Khan, M, Brand, F, Krawitz, P, Sleiman, PMA, Hakonarson, H, and Wei, Z (2021).
DeepCNV: a deep learning approach for authenticating copy number variations
Briefings in Bioinformatics, 22(5).

Hassanin, E, May, P, Aldisi, R, Krawitz, P, and Maj, C (2021).
Assessing the role of polygenic background on the penetrance of monogenic forms in Parkinson ' s disease Introduction :

Hassanin, E, May, P, Aldisi, R, Spier, I, Forstner, AJ, Nöthen, M, Aretz, S, Krawitz, P, Bobbili, DR, and Maj, C (2021).
Breast and prostate cancer risk : the interplay of polygenic risk , high-impact monogenic variants , and family history

Koutsouleris, N, Dwyer, DB, Degenhardt, F, Maj, C, Urquijo-Castro, MF, Sanfelici, R, Popovic, D, Oeztuerk, O, Haas, SS, Weiske, J, Ruef, A, Kambeitz-Ilankovic, L, Antonucci, LA, Neufang, S, Schmidt-Kraepelin, C, Ruhrmann, S, Penzel, N, Kambeitz, J, Haidl, TK, Rosen, M, Chisholm, K, Riecher-Rössler, A, Egloff, L, Schmidt, A, Andreou, C, Hietala, J, Schirmer, T, Romer, G, Walger, P, Franscini, M, Traber-Walker, N, Schimmelmann, BG, Flückiger, R, Michel, C, Rössler, W, Borisov, O, Krawitz, PM, Heekeren, K, Buechler, R, Pantelis, C, Falkai, P, Salokangas, RKR, Lencer, R, Bertolino, A, Borgwardt, S, Noethen, M, Brambilla, P, Wood, SJ, Upthegrove, R, Schultze-Lutter, F, Theodoridou, A, Meisenzahl, E, and Consortium, PRONIA (2021).
Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression
JAMA Psychiatry, 78(2):195--209.

Mallesh, N, Zhao, M, Meintker, L, Höllein, A, Elsner, F, Lüling, H, Haferlach, T, Kern, W, Westermann, J, Brossart, P, Krause, SW, and Krawitz, PM (2021).
Knowledge transfer to enhance the performance of deep learning models for automated classification of B cell neoplasms

Peng, C, Dieck, S, Schmid, A, Ahmad, A, Knaus, A, Wenzel, M, Mehnert, L, Zirn, B, Haack, T, Ossowski, S, Wagner, M, Brunet, T, Ehmke, N, Danyel, M, Rosnev, S, Kamphans, T, Nadav, G, Fleischer, N, Fröhlich, H, and Krawitz, P (2021).
CADA: Phenotype-driven gene prioritization based on a case-enriched knowledge graph

Rodríguez de los Santos, M, Rivalan, M, David, FS, Stumpf, A, Pitsch, J, Tsortouktzidis, D, Velasquez, LM, Voigt, A, Schilling, K, Mattei, D, Long, M, Vogt, G, Knaus, A, Fischer-Zirnsak, B, Wittler, L, Timmermann, B, Robinson, PN, Horn, D, Mundlos, S, Kornak, U, Becker, AJ, Schmitz, D, Winter, Y, and Krawitz, PM (2021).
A CRISPR-Cas9–engineered mouse model for GPI-anchor deficiency mirrors human phenotypes and exhibits hippocampal synaptic dysfunctions
Proceedings of the National Academy of Sciences, 118(2).

Wienbergen, H, Fach, A, Erdmann, J, Katalinic, A, Eisemann, N, Krawitz, P, Maj, C, Borisov, O, Munz, M, Noethen, M, Meyer-Saraei, R, Osteresch, R, Schmucker, J, Linke, A, Eitel, I, Hambrecht, R, and Langer, H (2021).
New technologies for intensive prevention programs after myocardial infarction: rationale and design of the NET-IPP trial
Clinical Research in Cardiology, 110(2):153--161.

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