22 results on '"Gogolewski K"'
Search Results
2. 176P Multiplex-immunoflourescence spatial patterns to predict triple-negative breast cancer molecular subtypes in the IMMUcan study
- Author
-
Garcia, A. Joaquin, primary, Krawczyk, J., additional, Rediti, M., additional, Gogolewski, K., additional, Możejko, M., additional, Tissot, S., additional, Rusakiewicz, S., additional, Despland, L., additional, Morfouace, M., additional, Liechti, R., additional, Marzetta, F., additional, Wang, X., additional, Vincent, D., additional, Goeminne, J-C., additional, Oliveira, J., additional, Hong, H.S., additional, Cesaroni, M., additional, Sotiriou, C., additional, Szczurek, E., additional, and Buisseret, L., additional
- Published
- 2023
- Full Text
- View/download PDF
3. 202P Discovery of immunological cellular neighborhoods from protein markers in spatial tumor data
- Author
-
Możejko, M., primary, Gogolewski, K., additional, Schulz, D., additional, Eling, N., additional, Krawczyk, J., additional, Możwiłło, A., additional, Daniel, M., additional, Staub, E., additional, Mourface, M., additional, Hong, H.S., additional, Bodenmiller, B., additional, and Szczurek, E., additional
- Published
- 2023
- Full Text
- View/download PDF
4. 199P Scalable multiplexed image analysis across cancer types as part of the IMMUcan consortium
- Author
-
Eling, N., primary, Dorier, J., additional, Rusakiewicz, S., additional, Tissot, S., additional, Devanand, P., additional, Daniel, M., additional, Déglise, S., additional, Palau Fernandez, B., additional, Windhager, J., additional, Możejko, M., additional, Gogolewski, K., additional, Krawczyk, J., additional, Essabbar, A., additional, Pancaldi, V., additional, Szczurek, E., additional, Morfouace, M., additional, Hong, H.S., additional, Liechti, R., additional, Bodenmiller, B., additional, and Schulz, D., additional
- Published
- 2023
- Full Text
- View/download PDF
5. Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- Author
-
Sherratt, K., primary, Gruson, H., additional, Grah, R., additional, Johnson, H., additional, Niehus, R., additional, Prasse, B., additional, Sandman, F., additional, Deuschel, J., additional, Wolffram, D., additional, Abbott, S., additional, Ullrich, A., additional, Gibson, G., additional, Ray, EL., additional, Reich, NG., additional, Sheldon, D., additional, Wang, Y., additional, Wattanachit, N., additional, Wang, L., additional, Trnka, J., additional, Obozinski, G., additional, Sun, T., additional, Thanou, D., additional, Pottier, L., additional, Krymova, E., additional, Barbarossa, MV., additional, Leithäuser, N., additional, Mohring, J., additional, Schneider, J., additional, Wlazlo, J., additional, Fuhrmann, J., additional, Lange, B., additional, Rodiah, I., additional, Baccam, P., additional, Gurung, H., additional, Stage, S., additional, Suchoski, B., additional, Budzinski, J., additional, Walraven, R., additional, Villanueva, I., additional, Tucek, V., additional, Šmíd, M., additional, Zajícek, M., additional, Pérez Álvarez, C., additional, Reina, B., additional, Bosse, NI., additional, Meakin, S., additional, Di Loro, P. Alaimo, additional, Maruotti, A., additional, Eclerová, V., additional, Kraus, A., additional, Kraus, D., additional, Pribylova, L., additional, Dimitris, B., additional, Li, ML., additional, Saksham, S., additional, Dehning, J., additional, Mohr, S., additional, Priesemann, V., additional, Redlarski, G., additional, Bejar, B., additional, Ardenghi, G., additional, Parolini, N., additional, Ziarelli, G., additional, Bock, W., additional, Heyder, S., additional, Hotz, T., additional, E. Singh, D., additional, Guzman-Merino, M., additional, Aznarte, JL., additional, Moriña, D., additional, Alonso, S., additional, Álvarez, E., additional, López, D., additional, Prats, C., additional, Burgard, JP., additional, Rodloff, A., additional, Zimmermann, T., additional, Kuhlmann, A., additional, Zibert, J., additional, Pennoni, F., additional, Divino, F., additional, Català, M., additional, Lovison, G., additional, Giudici, P., additional, Tarantino, B., additional, Bartolucci, F., additional, Jona Lasinio, G., additional, Mingione, M., additional, Farcomeni, A., additional, Srivastava, A., additional, Montero-Manso, P., additional, Adiga, A., additional, Hurt, B., additional, Lewis, B., additional, Marathe, M., additional, Porebski, P., additional, Venkatramanan, S., additional, Bartczuk, R., additional, Dreger, F., additional, Gambin, A., additional, Gogolewski, K., additional, Gruziel-Slomka, M., additional, Krupa, B., additional, Moszynski, A., additional, Niedzielewski, K., additional, Nowosielski, J., additional, Radwan, M., additional, Rakowski, F., additional, Semeniuk, M., additional, Szczurek, E., additional, Zielinski, J., additional, Kisielewski, J., additional, Pabjan, B., additional, Holger, K., additional, Kheifetz, Y., additional, Scholz, M., additional, Bodych, M., additional, Filinski, M., additional, Idzikowski, R., additional, Krueger, T., additional, Ozanski, T., additional, Bracher, J., additional, and Funk, S., additional
- Published
- 2022
- Full Text
- View/download PDF
6. A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave
- Author
-
Bracher, J, Wolffram, D, Deuschel, J, Görgen, K, Ketterer, JL, Ullrich, A, Abbott, S, Barbarossa, MV, Bertsimas, D, Bhatia, S, Bodych, M, Bosse, NI, Burgard, JP, Castro, L, Fairchild, G, Fuhrmann, J, Funk, S, Gogolewski, K, Gu, Q, Heyder, S, Hotz, T, Kheifetz, Y, Kirsten, H, Krueger, T, Krymova, E, Li, ML, Meinke, JH, Michaud, IJ, Niedzielewski, K, Ożański, T, Rakowski, F, Scholz, M, Soni, S, Srivastava, A, Zieliński, J, Zou, D, Gneiting, T, Schienle, M, and List of Contributors by Team
- Subjects
social sciences - Abstract
Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in Germany and Poland (12 October-19 December 2020). The study period covers the onset of the second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) and subsequently a decay (Poland) or plateau and renewed increase (Germany) in reported cases. Thirteen independent teams provided probabilistic real-time forecasts of COVID-19 cases and deaths. These were reported for lead times of one to four weeks, with evaluation focused on one- and two-week horizons, which are less affected by changing NPIs. Heterogeneity between forecasts was considerable both in terms of point predictions and forecast spread. Ensemble forecasts showed good relative performance, in particular in terms of coverage, but did not clearly dominate single-model predictions. The study was preregistered and will be followed up in future phases of the pandemic.
- Published
- 2021
7. Short-term forecasting of COVID-19 in Germany and Poland during the second wave – a preregistered study
- Author
-
Bracher, J., primary, Wolffram, D., additional, Deuschel, J., additional, Görgen, K., additional, Ketterer, J.L., additional, Ullrich, A., additional, Abbott, S., additional, Barbarossa, M.V., additional, Bertsimas, D., additional, Bhatia, S., additional, Bodych, M., additional, Bosse, N.I., additional, Burgard, J.P., additional, Castro, L., additional, Fairchild, G., additional, Fuhrmann, J., additional, Funk, S., additional, Gogolewski, K., additional, Gu, Q., additional, Heyder, S., additional, Hotz, T., additional, Kheifetz, Y., additional, Kirsten, H., additional, Krueger, T., additional, Krymova, E., additional, Li, M.L., additional, Meinke, J.H., additional, Michaud, I.J., additional, Niedzielewski, K., additional, Ożański, T., additional, Rakowski, F., additional, Scholz, M., additional, Soni, S., additional, Srivastava, A., additional, Zieliński, J., additional, Zou, D., additional, Gneiting, T., additional, and Schienle, M., additional
- Published
- 2020
- Full Text
- View/download PDF
8. Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- Author
-
Katharine Sherratt, Hugo Gruson, Rok Grah, Helen Johnson, Rene Niehus, Bastian Prasse, Frank Sandmann, Jannik Deuschel, Daniel Wolffram, Sam Abbott, Alexander Ullrich, Graham Gibson, Evan L Ray, Nicholas G Reich, Daniel Sheldon, Yijin Wang, Nutcha Wattanachit, Lijing Wang, Jan Trnka, Guillaume Obozinski, Tao Sun, Dorina Thanou, Loic Pottier, Ekaterina Krymova, Jan H Meinke, Maria Vittoria Barbarossa, Neele Leithäuser, Jan Mohring, Johanna Schneider, Jaroslaw Włazło, Jan Fuhrmann, Berit Lange, Isti Rodiah, Prasith Baccam, Heidi Gurung, Steven Stage, Bradley Suchoski, Jozef Budzinski, Robert Walraven, Inmaculada Villanueva, Vit Tucek, Martin Smid, Milan Zajíček, Cesar Pérez Álvarez, Borja Reina, Nikos I Bosse, Sophie R Meakin, Lauren Castro, Geoffrey Fairchild, Isaac Michaud, Dave Osthus, Pierfrancesco Alaimo Di Loro, Antonello Maruotti, Veronika Eclerová, Andrea Kraus, David Kraus, Lenka Pribylova, Bertsimas Dimitris, Michael Lingzhi Li, Soni Saksham, Jonas Dehning, Sebastian Mohr, Viola Priesemann, Grzegorz Redlarski, Benjamin Bejar, Giovanni Ardenghi, Nicola Parolini, Giovanni Ziarelli, Wolfgang Bock, Stefan Heyder, Thomas Hotz, David E Singh, Miguel Guzman-Merino, Jose L Aznarte, David Moriña, Sergio Alonso, Enric Álvarez, Daniel López, Clara Prats, Jan Pablo Burgard, Arne Rodloff, Tom Zimmermann, Alexander Kuhlmann, Janez Zibert, Fulvia Pennoni, Fabio Divino, Marti Català, Gianfranco Lovison, Paolo Giudici, Barbara Tarantino, Francesco Bartolucci, Giovanna Jona Lasinio, Marco Mingione, Alessio Farcomeni, Ajitesh Srivastava, Pablo Montero-Manso, Aniruddha Adiga, Benjamin Hurt, Bryan Lewis, Madhav Marathe, Przemyslaw Porebski, Srinivasan Venkatramanan, Rafal P Bartczuk, Filip Dreger, Anna Gambin, Krzysztof Gogolewski, Magdalena Gruziel-Słomka, Bartosz Krupa, Antoni Moszyński, Karol Niedzielewski, Jedrzej Nowosielski, Maciej Radwan, Franciszek Rakowski, Marcin Semeniuk, Ewa Szczurek, Jakub Zieliński, Jan Kisielewski, Barbara Pabjan, Holger Kirsten, Yuri Kheifetz, Markus Scholz, Przemyslaw Biecek, Marcin Bodych, Maciej Filinski, Radoslaw Idzikowski, Tyll Krueger, Tomasz Ozanski, Johannes Bracher, Sebastian Funk, Sherratt, K, Gruson, H, Grah, R, Johnson, H, Niehus, R, Prasse, B, Sandmann, F, Deuschel, J, Wolffram, D, Abbott, S, Ullrich, A, Gibson, G, L Ray, E, G Reich, N, Sheldon, D, Wang, Y, Wattanachit, N, Wang, L, Trnka, J, Obozinski, G, Sun, T, Thanou, D, Pottier, L, Krymova, E, H Meinke, J, Vittoria Barbarossa, M, Leithäuser, N, Mohring, J, Schneider, J, Włazło, J, Fuhrmann, J, Lange, B, Rodiah, I, Baccam, P, Gurung, H, Stage, S, Suchoski, B, Budzinski, J, Walraven, R, Villanueva, I, Tucek, V, Smid, M, Zajíček, M, Pérez Álvarez, C, Reina, B, I Bosse, N, R Meakin, S, Castro, L, Fairchild, G, Michaud, I, Osthus, D, Alaimo Di Loro, P, Maruotti, A, Eclerová, V, Kraus, A, Kraus, D, Pribylova, L, Dimitris, B, Lingzhi Li, M, Saksham, S, Dehning, J, Mohr, S, Priesemann, V, Redlarski, G, Bejar, B, Ardenghi, G, Parolini, N, Ziarelli, G, Bock, W, Heyder, S, Hotz, T, E Singh, D, Guzman-Merino, M, L Aznarte, J, Moriña, D, Alonso, S, Álvarez, E, López, D, Prats, C, Pablo Burgard, J, Rodloff, A, Zimmermann, T, Kuhlmann, A, Zibert, J, Pennoni, F, Divino, F, Català, M, Lovison, G, Giudici, P, Tarantino, B, Bartolucci, F, Jona Lasinio, G, Mingione, M, Farcomeni, A, Srivastava, A, Montero-Manso, P, Adiga, A, Hurt, B, Lewis, B, Marathe, M, Porebski, P, Venkatramanan, S, P Bartczuk, R, Dreger, F, Gambin, A, Gogolewski, K, Gruziel-Słomka, M, Krupa, B, Moszyński, A, Niedzielewski, K, Nowosielski, J, Radwan, M, Rakowski, F, Semeniuk, M, Szczurek, E, Zieliński, J, Kisielewski, J, Pabjan, B, Kirsten, H, Kheifetz, Y, Scholz, M, Biecek, P, Bodych, M, Filinski, M, Idzikowski, R, Krueger, T, Ozanski, T, Bracher, J, and Funk, S
- Subjects
epidemiology ,global health ,none ,General Immunology and Microbiology ,General Neuroscience ,mathematical modeling ,COVID-19 ,infectious diseases forecatsting ,General Medicine ,udc:616 ,General Biochemistry, Genetics and Molecular Biology ,COVID-19, Countries Predictions, Infectious disease, Multivariate Statistical Models, Short-term forecasts ,udc:616-036.22:519.876.5 ,SECS-S/01 - STATISTICA ,infectious diseases forecatsting, epidemiology, mathematical modeling, capacity planning, COVID-19, combining independent models, ensemble forecast ,ensemble forecast ,Settore SECS-S/01 ,napovedovanje nalezljivih bolezni, epidemiologija, matematično modeliranje, načrtovanje zmogljivosti, COVID-19, kombiniranje neodvisnih modelov, skupna napoved ,ddc:600 ,capacity planning ,combining independent models - Abstract
eLife 12, e81916 (2023). doi:10.7554/eLife.81916, Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022.Methods:We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results:Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.Conclusions:Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks., Published by eLife Sciences Publications, Cambridge
- Published
- 2023
9. PhaseDancer: a novel targeted assembler of segmental duplications unravels the complexity of the human chromosome 2 fusion going from 48 to 46 chromosomes in hominin evolution.
- Author
-
Poszewiecka B, Gogolewski K, Karolak JA, Stankiewicz P, and Gambin A
- Subjects
- Humans, Animals, Segmental Duplications, Genomic, Telomere, Genomics, Chromosomes, Human, Hominidae genetics
- Abstract
Resolving complex genomic regions rich in segmental duplications (SDs) is challenging due to the high error rate of long-read sequencing. Here, we describe a targeted approach with a novel genome assembler PhaseDancer that extends SD-rich regions of interest iteratively. We validate its robustness and efficiency using a golden-standard set of human BAC clones and in silico-generated SDs with predefined evolutionary scenarios. PhaseDancer enables extension of the incomplete complex SD-rich subtelomeric regions of Great Ape chromosomes orthologous to the human chromosome 2 (HSA2) fusion site, informing a model of HSA2 formation and unravelling the evolution of human and Great Ape genomes., (© 2023. BioMed Central Ltd., part of Springer Nature.)
- Published
- 2023
- Full Text
- View/download PDF
10. Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations.
- Author
-
Sherratt K, Gruson H, Grah R, Johnson H, Niehus R, Prasse B, Sandmann F, Deuschel J, Wolffram D, Abbott S, Ullrich A, Gibson G, Ray EL, Reich NG, Sheldon D, Wang Y, Wattanachit N, Wang L, Trnka J, Obozinski G, Sun T, Thanou D, Pottier L, Krymova E, Meinke JH, Barbarossa MV, Leithauser N, Mohring J, Schneider J, Wlazlo J, Fuhrmann J, Lange B, Rodiah I, Baccam P, Gurung H, Stage S, Suchoski B, Budzinski J, Walraven R, Villanueva I, Tucek V, Smid M, Zajicek M, Perez Alvarez C, Reina B, Bosse NI, Meakin SR, Castro L, Fairchild G, Michaud I, Osthus D, Alaimo Di Loro P, Maruotti A, Eclerova V, Kraus A, Kraus D, Pribylova L, Dimitris B, Li ML, Saksham S, Dehning J, Mohr S, Priesemann V, Redlarski G, Bejar B, Ardenghi G, Parolini N, Ziarelli G, Bock W, Heyder S, Hotz T, Singh DE, Guzman-Merino M, Aznarte JL, Morina D, Alonso S, Alvarez E, Lopez D, Prats C, Burgard JP, Rodloff A, Zimmermann T, Kuhlmann A, Zibert J, Pennoni F, Divino F, Catala M, Lovison G, Giudici P, Tarantino B, Bartolucci F, Jona Lasinio G, Mingione M, Farcomeni A, Srivastava A, Montero-Manso P, Adiga A, Hurt B, Lewis B, Marathe M, Porebski P, Venkatramanan S, Bartczuk RP, Dreger F, Gambin A, Gogolewski K, Gruziel-Slomka M, Krupa B, Moszyński A, Niedzielewski K, Nowosielski J, Radwan M, Rakowski F, Semeniuk M, Szczurek E, Zielinski J, Kisielewski J, Pabjan B, Holger K, Kheifetz Y, Scholz M, Przemyslaw B, Bodych M, Filinski M, Idzikowski R, Krueger T, Ozanski T, Bracher J, and Funk S
- Subjects
- Humans, Forecasting, Models, Statistical, Retrospective Studies, Communicable Diseases, COVID-19 diagnosis, COVID-19 epidemiology, Epidemics
- Abstract
Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022., Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1-4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models' predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models' forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models' past predictive performance., Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models' forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models' forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models' forecasts of deaths (N=763 predictions from 20 models). Across a 1-4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models., Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks., Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 (https://www.nfdi4health.de/task-force-covid-19-2) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z)., Competing Interests: KS, HG, RG, HJ, RN, BP, FS, JD, DW, SA, AU, GG, ER, NR, DS, YW, NW, LW, JT, GO, TS, DT, LP, EK, JM, MB, NL, JM, JS, JW, JF, BL, IR, JB, RW, IV, VT, MS, MZ, CP, BR, NB, SM, LC, GF, IM, DO, PA, AM, VE, AK, DK, LP, BD, ML, SS, JD, SM, VP, GR, BB, GA, NP, GZ, WB, SH, TH, DS, MG, JA, DM, SA, EA, DL, CP, JB, AR, TZ, AK, JZ, FP, FD, MC, GL, PG, BT, FB, GJ, MM, AF, AS, PM, AA, BH, BL, MM, PP, SV, RB, FD, AG, KG, MG, BK, AM, KN, JN, MR, FR, MS, ES, JZ, JK, BP, KH, YK, MS, BP, MB, MF, RI, TK, TO, JB, SF No competing interests declared, PB, HG, SS, BS Affiliated with IEM, Inc. The author has no financial interests to declare
- Published
- 2023
- Full Text
- View/download PDF
11. National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021.
- Author
-
Bracher J, Wolffram D, Deuschel J, Görgen K, Ketterer JL, Ullrich A, Abbott S, Barbarossa MV, Bertsimas D, Bhatia S, Bodych M, Bosse NI, Burgard JP, Castro L, Fairchild G, Fiedler J, Fuhrmann J, Funk S, Gambin A, Gogolewski K, Heyder S, Hotz T, Kheifetz Y, Kirsten H, Krueger T, Krymova E, Leithäuser N, Li ML, Meinke JH, Miasojedow B, Michaud IJ, Mohring J, Nouvellet P, Nowosielski JM, Ozanski T, Radwan M, Rakowski F, Scholz M, Soni S, Srivastava A, Gneiting T, and Schienle M
- Abstract
Background: During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021., Methods: We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study., Results: We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict., Conclusions: Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance., (© 2022. The Author(s).)
- Published
- 2022
- Full Text
- View/download PDF
12. Revised time estimation of the ancestral human chromosome 2 fusion.
- Author
-
Poszewiecka B, Gogolewski K, Stankiewicz P, and Gambin A
- Subjects
- Animals, Centromere genetics, Chromosomes, Human, Genome, Humans, Evolution, Molecular, Hominidae genetics
- Abstract
Background: The reduction of the chromosome number from 48 in the Great Apes to 46 in modern humans is thought to result from the end-to-end fusion of two ancestral non-human primate chromosomes forming the human chromosome 2 (HSA2). Genomic signatures of this event are the presence of inverted telomeric repeats at the HSA2 fusion site and a block of degenerate satellite sequences that mark the remnants of the ancestral centromere. It has been estimated that this fusion arose up to 4.5 million years ago (Mya)., Results: We have developed an enhanced algorithm for the detection and efficient counting of the locally over-represented weak-to-strong (AT to GC) substitutions. By analyzing the enrichment of these substitutions around the fusion site of HSA2 we estimated its formation time at 0.9 Mya with a 95% confidence interval of 0.4-1.5 Mya. Additionally, based on the statistics derived from our algorithm, we have reconstructed the evolutionary distances among the Great Apes (Hominoidea)., Conclusions: Our results shed light on the HSA2 fusion formation and provide a novel computational alternative for the estimation of the speciation chronology., (© 2022. The Author(s).)
- Published
- 2022
- Full Text
- View/download PDF
13. TADeus2: a web server facilitating the clinical diagnosis by pathogenicity assessment of structural variations disarranging 3D chromatin structure.
- Author
-
Poszewiecka B, Pienkowski VM, Nowosad K, Robin JD, Gogolewski K, and Gambin A
- Subjects
- Humans, Chromosomes, Genome, Human, Chromatin genetics, DNA
- Abstract
In recent years great progress has been made in identification of structural variants (SV) in the human genome. However, the interpretation of SVs, especially located in non-coding DNA, remains challenging. One of the reasons stems in the lack of tools exclusively designed for clinical SVs evaluation acknowledging the 3D chromatin architecture. Therefore, we present TADeus2 a web server dedicated for a quick investigation of chromatin conformation changes, providing a visual framework for the interpretation of SVs affecting topologically associating domains (TADs). This tool provides a convenient visual inspection of SVs, both in a continuous genome view as well as from a rearrangement's breakpoint perspective. Additionally, TADeus2 allows the user to assess the influence of analyzed SVs within flaking coding/non-coding regions based on the Hi-C matrix. Importantly, the SVs pathogenicity is quantified and ranked using TADA, ClassifyCNV tools and sampling-based P-value. TADeus2 is publicly available at https://tadeus2.mimuw.edu.pl., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)
- Published
- 2022
- Full Text
- View/download PDF
14. Data-driven case fatality rate estimation for the primary lineage of SARS-CoV-2 in Poland.
- Author
-
Gogolewski K, Miasojedow B, Sadkowska-Todys M, Stepień M, Demkow U, Lech A, Szczurek E, Rabczenko D, Rosińska M, and Gambin A
- Subjects
- Contact Tracing, Humans, Pandemics, Poland epidemiology, COVID-19 epidemiology, SARS-CoV-2
- Abstract
After more than one and a half year since the COVID-19 pandemics outbreak the scientific world is constantly trying to understand its dynamics. In this paper of the case fatality rates (CFR) for COVID-19 we study the historic data regarding mortality in Poland during the first six months of pandemic, when no SARS-CoV-2 variants of concern were present among infected. To this end, we apply competing risk models to perform both uni- and multivariate analyses on specific subpopulations selected by different factors including the key indicators: age, sex, hospitalization. The study explores the case fatality rate to find out its decreasing trend in time. Furthermore, we describe the differences in mortality among hospitalized and other cases indicating a sudden increase of mortality among hospitalized cases at the end of the 2020 spring season. Exploratory and multivariate analysis revealed the real impact of each variable and besides the expected factors indicating increased mortality (age, comorbidities) we track more non-obvious indicators. Recent medical care as well as the identification of the source contact, independently of the comorbidities, significantly impact an individual mortality risk. As a result, the study provides a twofold insight into the COVID-19 mortality in Poland. On one hand we explore mortality in different groups with respect to different variables, on the other we indicate novel factors that may be crucial in reducing mortality. The later can be coped, e.g. by more efficient contact tracing and proper organization and management of the health care system to accompany those who need medical care independently of comorbidities or COVID-19 infection., (Copyright © 2022 Elsevier Inc. All rights reserved.)
- Published
- 2022
- Full Text
- View/download PDF
15. Risk assessment of COVID-19 epidemic resurgence in relation to SARS-CoV-2 variants and vaccination passes.
- Author
-
Krueger T, Gogolewski K, Bodych M, Gambin A, Giordano G, Cuschieri S, Czypionka T, Perc M, Petelos E, Rosińska M, and Szczurek E
- Abstract
The introduction of COVID-19 vaccination passes (VPs) by many countries coincided with the Delta variant fast becoming dominant across Europe. A thorough assessment of their impact on epidemic dynamics is still lacking. Here, we propose the VAP-SIRS model that considers possibly lower restrictions for the VP holders than for the rest of the population, imperfect vaccination effectiveness against infection, rates of (re-)vaccination and waning immunity, fraction of never-vaccinated, and the increased transmissibility of the Delta variant. Some predicted epidemic scenarios for realistic parameter values yield new COVID-19 infection waves within two years, and high daily case numbers in the endemic state, even without introducing VPs and granting more freedom to their holders. Still, suitable adaptive policies can avoid unfavorable outcomes. While VP holders could initially be allowed more freedom, the lack of full vaccine effectiveness and increased transmissibility will require accelerated (re-)vaccination, wide-spread immunity surveillance, and/or minimal long-term common restrictions., Competing Interests: Competing interestsOther projects in the research lab of E.S. are co-funded by Merck Healthcare KGaA. The remaining authors declare no competing interests., (© The Author(s) 2022.)
- Published
- 2022
- Full Text
- View/download PDF
16. A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave.
- Author
-
Bracher J, Wolffram D, Deuschel J, Görgen K, Ketterer JL, Ullrich A, Abbott S, Barbarossa MV, Bertsimas D, Bhatia S, Bodych M, Bosse NI, Burgard JP, Castro L, Fairchild G, Fuhrmann J, Funk S, Gogolewski K, Gu Q, Heyder S, Hotz T, Kheifetz Y, Kirsten H, Krueger T, Krymova E, Li ML, Meinke JH, Michaud IJ, Niedzielewski K, Ożański T, Rakowski F, Scholz M, Soni S, Srivastava A, Zieliński J, Zou D, Gneiting T, and Schienle M
- Subjects
- COVID-19 virology, Forecasting, Germany epidemiology, Humans, Models, Statistical, Pandemics statistics & numerical data, Poland epidemiology, SARS-CoV-2 physiology, Seasons, COVID-19 epidemiology
- Abstract
Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in Germany and Poland (12 October-19 December 2020). The study period covers the onset of the second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) and subsequently a decay (Poland) or plateau and renewed increase (Germany) in reported cases. Thirteen independent teams provided probabilistic real-time forecasts of COVID-19 cases and deaths. These were reported for lead times of one to four weeks, with evaluation focused on one- and two-week horizons, which are less affected by changing NPIs. Heterogeneity between forecasts was considerable both in terms of point predictions and forecast spread. Ensemble forecasts showed good relative performance, in particular in terms of coverage, but did not clearly dominate single-model predictions. The study was preregistered and will be followed up in future phases of the pandemic., (© 2021. The Author(s).)
- Published
- 2021
- Full Text
- View/download PDF
17. Harvest time affects antioxidant capacity, total polyphenol and flavonoid content of Polish St John's wort's (Hypericum perforatum L.) flowers.
- Author
-
Makarova K, Sajkowska-Kozielewicz JJ, Zawada K, Olchowik-Grabarek E, Ciach MA, Gogolewski K, Dobros N, Ciechowicz P, Freichels H, and Gambin A
- Subjects
- Anthracenes chemistry, Antioxidants pharmacology, Benzhydryl Compounds chemistry, Ethanol chemistry, Humans, Perylene analogs & derivatives, Perylene chemistry, Phenols chemistry, Phloroglucinol analogs & derivatives, Phloroglucinol chemistry, Plant Extracts pharmacology, Poland, Polyphenols pharmacology, Principal Component Analysis, Terpenes chemistry, Antioxidants chemistry, Flavonoids chemistry, Flowers chemistry, Hypericum chemistry, Plant Extracts chemistry, Polyphenols chemistry
- Abstract
The polyphenol content and antioxidant capacity of hyperforin and hypericin-standardized H. perforatum L. extracts may vary due to the harvest time. In this work, ethanol and ethanol-water extracts of air-dried and lyophilized flowers of H. perforatum L., collected throughout a vegetation season in central Poland, were studied. Air-dried flowers extracts had higher polyphenol (371 mg GAE/g) and flavonoid (160 mg CAE/g) content, DPPH radical scavenging (1672 mg DPPH/g), ORAC (5214 µmol TE/g) and FRAP (2.54 mmol Fe
2+ /g) than lyophilized flowers extracts (238 mg GAE/g, 107 mg CAE/g, 1287 mg DPPH/g, 3313 µmol TE/g and 0.31 mmol Fe2+ /g, respectively). Principal component analysis showed that the collection date influenced the flavonoid and polyphenol contents and FRAP of ethanol extracts, and DPPH and ORAC values of ethanol-water extracts. The ethanol extracts with the highest polyphenol and flavonoid content protected human erythrocytes against bisphenol A-induced damage. Both high field and benchtop NMR spectra of selected extracts, revealed differences in composition caused by extraction solvent and raw material collection date. Moreover, we have shown that benchtop NMR can be used to detect the compositional variation of extracts if the assignment of signals is done previously.- Published
- 2021
- Full Text
- View/download PDF
18. Low Entropy Sub-Networks Prevent the Integration of Metabolomic and Transcriptomic Data.
- Author
-
Gogolewski K, Kostecki M, and Gambin A
- Abstract
The constantly and rapidly increasing amount of the biological data gained from many different high-throughput experiments opens up new possibilities for data- and model-driven inference. Yet, alongside, emerges a problem of risks related to data integration techniques. The latter are not so widely taken account of. Especially, the approaches based on the flux balance analysis (FBA) are sensitive to the structure of a metabolic network for which the low-entropy clusters can prevent the inference from the activity of the metabolic reactions. In the following article, we set forth problems that may arise during the integration of metabolomic data with gene expression datasets. We analyze common pitfalls, provide their possible solutions, and exemplify them by a case study of the renal cell carcinoma (RCC). Using the proposed approach we provide a metabolic description of the known morphological RCC subtypes and suggest a possible existence of the poor-prognosis cluster of patients, which are commonly characterized by the low activity of the drug transporting enzymes crucial in the chemotherapy. This discovery suits and extends the already known poor-prognosis characteristics of RCC. Finally, the goal of this work is also to point out the problem that arises from the integration of high-throughput data with the inherently nonuniform, manually curated low-throughput data. In such cases, the over-represented information may potentially overshadow the non-trivial discoveries.
- Published
- 2020
- Full Text
- View/download PDF
19. Truncated Robust Principal Component Analysis and Noise Reduction for Single Cell RNA Sequencing Data.
- Author
-
Gogolewski K, Sykulski M, Chung NC, and Gambin A
- Subjects
- Humans, Algorithms, Databases, Nucleic Acid, Sequence Analysis, RNA, Single-Cell Analysis
- Abstract
The development of single cell RNA sequencing (scRNA-seq) has enabled innovative approaches to investigating mRNA abundances. In our study, we are interested in extracting the systematic patterns of scRNA-seq data in an unsupervised manner; thus, we have developed two extensions of robust principal component analysis (RPCA). First, we present a truncated version of RPCA (tRPCA), which is much faster and memory efficient. Second, we introduce a noise reduction in tRPCA with L
2 regularization. Unlike RPCA that only considers a low-rank L and sparse S matrices, the proposed method can also extract a noise E matrix inherent in modern genomic data. We demonstrate its usefulness by applying our methods on the peripheral blood mononuclear cell scRNA-seq data. Particularly, the clustering of a low-rank L matrix showcases better classification of unlabeled single cells. Overall, the proposed variants are well suited for high-dimensional and noisy data that are routinely generated in genomics.- Published
- 2019
- Full Text
- View/download PDF
20. Inferring Molecular Processes Heterogeneity from Transcriptional Data.
- Author
-
Gogolewski K, Wronowska W, Lech A, Lesyng B, and Gambin A
- Subjects
- Cell Line, Tumor, Computational Biology methods, Down-Regulation genetics, Gene Expression Profiling methods, Humans, Oligonucleotide Array Sequence Analysis methods, RNA genetics, Signal Transduction genetics, Gene Regulatory Networks genetics, Transcription, Genetic genetics, Transcriptome genetics
- Abstract
RNA microarrays and RNA-seq are nowadays standard technologies to study the transcriptional activity of cells. Most studies focus on tracking transcriptional changes caused by specific experimental conditions. Information referring to genes up- and downregulation is evaluated analyzing the behaviour of relatively large population of cells by averaging its properties. However, even assuming perfect sample homogeneity, different subpopulations of cells can exhibit diverse transcriptomic profiles, as they may follow different regulatory/signaling pathways. The purpose of this study is to provide a novel methodological scheme to account for possible internal, functional heterogeneity in homogeneous cell lines, including cancer ones. We propose a novel computational method to infer the proportion between subpopulations of cells that manifest various functional behaviour in a given sample. Our method was validated using two datasets from RNA microarray experiments. Both experiments aimed to examine cell viability in specific experimental conditions. The presented methodology can be easily extended to RNA-seq data as well as other molecular processes. Moreover, it complements standard tools to indicate most important networks from transcriptomic data and in particular could be useful in the analysis of cancer cell lines affected by biologically active compounds or drugs.
- Published
- 2017
- Full Text
- View/download PDF
21. Lethal lung hypoplasia and vascular defects in mice with conditional Foxf1 overexpression.
- Author
-
Dharmadhikari AV, Sun JJ, Gogolewski K, Carofino BL, Ustiyan V, Hill M, Majewski T, Szafranski P, Justice MJ, Ray RS, Dickinson ME, Kalinichenko VV, Gambin A, and Stankiewicz P
- Abstract
FOXF1 heterozygous point mutations and genomic deletions have been reported in newborns with the neonatally lethal lung developmental disorder, alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV). However, no gain-of-function mutations in FOXF1 have been identified yet in any human disease conditions. To study the effects of FOXF1 overexpression in lung development, we generated a Foxf1 overexpression mouse model by knocking-in a Cre-inducible Foxf1 allele into the ROSA26 (R26) locus. The mice were phenotyped using micro-computed tomography (micro-CT), head-out plethysmography, ChIP-seq and transcriptome analyses, immunohistochemistry, and lung histopathology. Thirty-five percent of heterozygous R26-Lox-Stop-Lox (LSL)-Foxf1 embryonic day (E)15.5 embryos exhibit subcutaneous edema, hemorrhages and die perinatally when bred to Tie2-cre mice, which targets Foxf1 overexpression to endothelial and hematopoietic cells. Histopathological and micro-CT evaluations revealed that R26Foxf1; Tie2-cre embryos have immature lungs with a diminished vascular network. Neonates exhibited respiratory deficits verified by detailed plethysmography studies. ChIP-seq and transcriptome analyses in E18.5 lungs identified Sox11, Ghr, Ednrb, and Slit2 as potential downstream targets of FOXF1. Our study shows that overexpression of the highly dosage-sensitive Foxf1 impairs lung development and causes vascular abnormalities. This has important clinical implications when considering potential gene therapy approaches to treat disorders of FOXF1 abnormal dosage, such as ACDMPV., Competing Interests: The authors declare no competing or financial interests., (© 2016. Published by The Company of Biologists Ltd.)
- Published
- 2016
- Full Text
- View/download PDF
22. Molecular and clinical analyses of 16q24.1 duplications involving FOXF1 identify an evolutionarily unstable large minisatellite.
- Author
-
Dharmadhikari AV, Gambin T, Szafranski P, Cao W, Probst FJ, Jin W, Fang P, Gogolewski K, Gambin A, George-Abraham JK, Golla S, Boidein F, Duban-Bedu B, Delobel B, Andrieux J, Becker K, Holinski-Feder E, Cheung SW, and Stankiewicz P
- Subjects
- Abnormalities, Multiple pathology, Adolescent, Animals, Child, Preschool, Evolution, Molecular, Female, Gene Dosage, Humans, Male, Middle Aged, Minisatellite Repeats, Pedigree, Abnormalities, Multiple genetics, Chromosomes, Human, Pair 16 genetics, Forkhead Transcription Factors genetics, Gene Duplication
- Abstract
Background: Point mutations or genomic deletions of FOXF1 result in a lethal developmental lung disease Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins. However, the clinical consequences of the constitutively increased dosage of FOXF1 are unknown., Methods: Copy-number variations and their parental origin were identified using a combination of array CGH, long-range PCR, DNA sequencing, and microsatellite analyses. Minisatellite sequences across different species were compared using a gready clustering algorithm and genome-wide analysis of the distribution of minisatellite sequences was performed using R statistical software., Results: We report four unrelated families with 16q24.1 duplications encompassing entire FOXF1. In a 4-year-old boy with speech delay and a café-au-lait macule, we identified an ~15 kb 16q24.1 duplication inherited from the reportedly healthy father, in addition to a de novo ~1.09 Mb mosaic 17q11.2 NF1 deletion. In a 13-year-old patient with autism and mood disorder, we found an ~0.3 Mb duplication harboring FOXF1 and an ~0.5 Mb 16q23.3 duplication, both inherited from the father with bipolar disorder. In a 47-year old patient with pyloric stenosis, mesenterium commune, and aplasia of the appendix, we identified an ~0.4 Mb duplication in 16q24.1 encompassing 16 genes including FOXF1. The patient transmitted the duplication to her daughter, who presented with similar symptoms. In a fourth patient with speech and motor delay, and borderline intellectual disability, we identified an ~1.7 Mb FOXF1 duplication adjacent to a large minisatellite. This duplication has a complex structure and arose de novo on the maternal chromosome, likely as a result of a DNA replication error initiated by the adjacent large tandem repeat. Using bioinformatic and array CGH analyses of the minisatellite, we found a large variation of its size in several different species and individuals, demonstrating both its evolutionarily instability and population polymorphism., Conclusions: Our data indicate that constitutional duplication of FOXF1 in humans is not associated with any pediatric lung abnormalities. We propose that patients with gut malrotation, pyloric or duodenal stenosis, and gall bladder agenesis should be tested for FOXF1 alterations. We suggest that instability of minisatellites greater than 1 kb can lead to structural variation due to DNA replication errors.
- Published
- 2014
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.