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a.SAP verarbeitet Berufspraktikum für Bioinformatik ( 19402433 )

Feld Evento Lehrplanung Operationen
Dozent Kein Eintrag

Tim Conrad

a.Absage verarbeitet Reaktions-Diffusions-Simulationen für Signaltransduktionskaskaden ( 19402311 )

Feld Evento Lehrplanung Operationen
Dozent Kein Eintrag

Frank Noe

Evento: eVV-Textfeld "Leitung (Publikation)" Evento: Dozierende (6 Lektionen) Lehrplanung
Dozierende in eVV
Frank Noe
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Frank Noe

a.SAP verarbeitet Projektmanagement im Softwarebereich (Functional Genomics with R) ( 19402513 )

Feld Evento Lehrplanung Operationen
Kapazität 9 8
Dozent Kein Eintrag

Robert Schöpflin

Alena van Bömmel

a.Publiziert Mentoring Bioinformatik ( 19404146 )

Feld Evento Lehrplanung Operationen
Dozent Kein Eintrag

Ulrike Seyferth

Evento: eVV-Textfeld "Leitung (Publikation)" Evento: Dozierende (25 Lektionen) Lehrplanung
Dozierende in eVV
Ulrike Seyferth
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Ulrike Seyferth

a.SAP verarbeitet Projektmanagement im Softwarebereich (OpenMS) ( 19403413 )

Feld Evento Lehrplanung Operationen
Dozent Kein Eintrag

Chris Bielow

a.SAP verarbeitet Forschungspraktikum Bioinformatik ( 19400432 )

Feld Evento Lehrplanung Operationen
Dozent

Katja Nowick

Rosario Piro

Dorothee Günzel

Robert Preissner

Heike Siebert

Frank Noe

Bernhard Renard

Tim Conrad

Priyanka Banerjee

Alexander Bockmayr

Martin Vingron

Irmtraud Meyer

Knut Reinert

Camila Mazzoni

Evento: eVV-Textfeld "Leitung (Publikation)" Evento: Dozierende (1 Lektionen) Lehrplanung
Dozierende in eVV
Camila Mazzoni
Irmtraud Meyer
Robert Preissner
Alexander Bockmayr
Martin Vingron
Priyanka Banerjee
Rosario Piro
Bernhard Renard
Tim Conrad
Knut Reinert
Dorothee Günzel
Katja Nowick
Frank Noe
Heike Siebert
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Katja Nowick
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Camila Mazzoni
Irmtraud Meyer
Robert Preissner
Alexander Bockmayr
Martin Vingron
Priyanka Banerjee
Rosario Piro
Bernhard Renard
Tim Conrad
Knut Reinert
Dorothee Günzel
Frank Noe
Heike Siebert

a.SAP verarbeitet Mathematik für Bioinformatiker II ( 19402201 )

Feld Evento Lehrplanung Operationen
Submodul

0260cA2.2.1

0521aA2.4.1

0260cA.2.2.1

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Evento: eVV-Textfeld "Leitung (Publikation)" Evento: Dozierende (30 Lektionen) Lehrplanung
Dozierende in eVV
Alexander Bockmayr
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Alexander Bockmayr
Heike Siebert
Alexander Bockmayr
Heike Siebert

a.SAP verarbeitet Projektmanagement im Softwarebereich (Synthetische Biologie) ( 19402013 )

Feld Evento Lehrplanung Operationen
Kapazität 7 6
Dozent Kein Eintrag

Melania Nowicka

Heike Siebert

a.SAP verarbeitet Übung zu Mathematik für Bioinformatiker II ( 19402202 )

Feld Evento Lehrplanung Operationen
Submodul

0260cA2.2.2

0521aA2.4.2

0260cA.2.2.2

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Dozent

Alexander Bockmayr

Heike Siebert

Frederik Laszlo Wieder

Frederik Laszlo Wieder

Evento: eVV-Textfeld "Leitung (Publikation)" Evento: Dozierende (53 Lektionen) Lehrplanung
Dozierende in eVV
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Frederik Laszlo Wieder
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Alexander Bockmayr
Frederik Laszlo Wieder
Heike Siebert
Frederik Laszlo Wieder

a.SAP verarbeitet Seminar zu Projektmanagement im Softwarebereich (Synthetische Biologie) ( 19402011 )

Feld Evento Lehrplanung Operationen
Kapazität 7 6
Dozent Kein Eintrag

Melania Nowicka

Heike Siebert

a.SAP verarbeitet Seminar zu Projektmanagement im Softwarebereich (Functional Genomics with R) ( 19402511 )

Feld Evento Lehrplanung Operationen
Kapazität 9 8
Dozent Kein Eintrag

Robert Schöpflin

Alena van Bömmel

a.SAP verarbeitet Seminar zu Projektmanagement im Softwarebereich (Workflows) ( 19404311 )

Feld Evento Lehrplanung Operationen
Kapazität 7 6
Dozent Kein Eintrag

Sandro Andreotti

a.SAP verarbeitet Seminar zu Projektmanagement im Softwarebereich (OpenMS) ( 19403411 )

Feld Evento Lehrplanung Operationen
Dozent Kein Eintrag

Chris Bielow

a.SAP verarbeitet Übung zu Complex Systems in Bioinformatics ( 19405202 )

Feld Evento Lehrplanung Operationen
Submodul

0262bB1.3.2

0262cB1.1.2

0590aB1.32.2

0262bB.1.3.2

0262cB.1.1.2

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a.SAP verarbeitet Seminar zu Complex Systems in Bioinformatics ( 19405211 )

Feld Evento Lehrplanung Operationen
Submodul

0262bB1.3.3

0262cB1.1.3

0590aB1.32.3

0262bB.1.3.3

0262cB.1.1.3

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a.SAP verarbeitet Complex Systems in Bioinformatics ( 19405201 )

Feld Evento Lehrplanung Operationen
Submodul

0262bB1.3.1

0262cB1.1.1

0590aB1.32.1

0262bB.1.3.1

0262cB.1.1.1

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a.SAP verarbeitet Ethics and Policy Questions ( 19405413 )

Feld Evento Lehrplanung Operationen
Dozent

Tim Conrad

Jens Peter Fürste

Jochen Kruppa

Tim Conrad

a.SAP verarbeitet Data Science in the Life Sciences ( 19405606 )

Feld Evento
Textunterschiede
 Lehrplanung Operationen
Englische Beschreibung <p>This course offers an introduction to various types of data and analysis techniques which are typically used in the life sciences (e.g. omics technologies). The goal is to get a deeper understanding of advanced concepts and data analytical methods in the area of life sciences.</p> <p>The focus will be on the following topics:</p> <ul> <li>acquisition and pre-processing of data from the area of life sciences,</li> <li>explorative analysis techniques,</li> <li>concepts and tools for reproducible research,</li> <li>theory and practice of methods and models for the analysis of data from the life sciences (statistical inference, regression models, methods of machine learning),</li> <li>introduction to methods of big data analysis.</li> </ul> <p>After successful completion of this course, participants are able to evaluate, plan and conduct investigations in the life sciences using common methods.</p> <p>&nbsp;</p> <p>This course offers an introduction to various types of data and analysis techniques which are typically used in the life sciences (e.g. omics technologies). The goal is to get a deeper understanding of advanced concepts and data analytical methods in the area of life sciences.</p> <p>The focus will be on the following topics:</p> <ulp> * <li>acquisition and pre-processing of data from the area of life sciences,</libr> * <li>explorative analysis techniques,</libr> * <li>concepts and tools for reproducible research,</libr> * <li>theory and practice of methods and models for the analysis of data from the life sciences (statistical inference, regression models, methods of machine learning),</libr> * <li>introduction to methods of big data analysis.</li> </ulp> <p>After successful completion of this course, participants are able to evaluate, plan and conduct investigations in the life sciences using common methods.</p> <p> </p> <p>This course offers an introduction to various types of data and analysis techniques which are typically used in the life sciences (e.g. omics technologies). The goal is to get a deeper understanding of advanced concepts and data analytical methods in the area of life sciences.</p> <p>The focus will be on the following topics:</p> <p>* acquisition and pre-processing of data from the area of life sciences,<br /> * explorative analysis techniques,<br /> * concepts and tools for reproducible research,<br /> * theory and practice of methods and models for the analysis of data from the life sciences (statistical inference, regression models, methods of machine learning),<br /> * introduction to methods of big data analysis.</p> <p>After successful completion of this course, participants are able to evaluate, plan and conduct investigations in the life sciences using common methods.</p> <p>&nbsp;</p>
Submodul

0590aB2.1.1

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a.Absage verarbeitet Phylogeny Inference and Application ( 19405501 )

Feld Evento Textunterschiede Lehrplanung Operationen
Beschreibung <p>Siehe englische Beschreibung.</p> <p>Siehe englische Bdeschreibuption in Eng.lish</p> <ol> </ol> <p>See description in English</p> <ol> </ol>
Englische Beschreibung <div><strong>Course content:&nbsp;</strong></div> <div>The course is thematically divided into two parts:</div> <div>&nbsp;</div> <div><em>Inferring evolutionary relationships:</em></div> <div>Methods for inferring phylogenetic trees will be introduced using the following&nbsp;topics</div> <div> <ol> <li>Mechanisms of genome evolution</li> <li>Combinatorial optimization problems in phylogenetic tree inference&nbsp;</li> <li>Using minimum spanning trees to infer large phylogenetic&nbsp;trees</li> <li>Methods for rooting phylogenetic trees</li> <li>Limitations of phylogenetic trees, and alternate network-based models</li> </ol> </div> <div><em>Learning evolutionary dynamics using trees:</em></div> <div>Additionally, we will cover applications of phylogenetic trees such as&nbsp;</div> <div> <ol> <li>Time-calibrated trees using molecular clocks</li> <li>Identifying genomic regions under selection</li> <li>Inferring migration history</li> <li>Virus epidemiology</li> <li>Tumor heterogeneity</li> </ol> </div> <div dir="ltr"><strong>Prerequisites: </strong></div> <div dir="ltr">The course is designed for bioinformaticians, and computer scientists interested in biology.&nbsp;</div> <div dir="ltr">&nbsp;</div> <div>Students will be using current software for their tutorials (Uebungen). Programming assignments are expected to be submitted as jupyter notebooks.&nbsp;</div> <div>A familiarity with python is helpful but not necessary as it will be covered in the initial tutorials.</div> <div> <p>Siehe englische Beschreibung.</p> <p> </p> <p><strong>Course content: </strong></div> <div> The course is thematically divided into two parts:</divp> <div> </div> <divp><em>Inferring evolutionary relationships:</em> </divp> <dol> <liv>Metchodanisms for inferring phylogenetic treomes will be intrvoduced lusting the following topics</div> <dliv> <ol> <li>Modechanismls of genome evolsubstitution</li> <li>Combinatorial optimization problems in for phylogenetic tree inference </li> <li>Using minimum spanning trees to infer large phylogenetic trees</li> <li>Methods for rooting phylogenetic trees</li> <li>LUsing mitnimum spatnniong trees to infer large phylogenetic  trees, and alternate network-based models</li> </ol> </div> <divp><em>Learning evolutionary dynamics using trees:</em> </divp> <divp>Additionally, we will cover applications of phylogenetic trees such as </divp> <div> <ol> <li>Time-calibrated trees using molecular clocks</li> <li>Identifying genomic regions under selection</li> <li>Inferring migration history</li> <li>ViMolecularus epidemiology</li> <li>Tumorf heterogeneity</li> </ol> </div> <div dir="ltr"><strong>Prerequisites: </strong></dliv> <div dir="<ltr"i>The course is dGesigned for bioinformaticians, band computer scientists interested in biology. </div> <divf dir="ltr"> </div> <div>Students will be using cmourrent software fvor their tlutorials (Uebungen). Programming assignments are expected to be submitted as jupyter notebooks. </dliv> <div>A familiarity with python is helpful but not necessary as it will be c/overed in the initial tutorials.> </div> <div> <p>Siehe englische Beschreibung.</p> <p>&nbsp;</p> <p><strong>Course content:&nbsp;</strong>&nbsp;The course is thematically divided into two parts:</p> <p><em>Inferring evolutionary relationships:</em>&nbsp;</p> <ol> <li>Mechanisms of genome evolution</li> <li>Models of gene substitution</li> <li>Combinatorial optimization problems for&nbsp;phylogenetic tree inference&nbsp;</li> <li>Methods for rooting phylogenetic trees</li> <li>Using minimum spanning trees to infer large phylogenetic&nbsp;trees</li> </ol> <p><em>Learning evolutionary dynamics using trees:</em>&nbsp;</p> <p>Additionally, we will cover applications of phylogenetic trees such as&nbsp;</p> <ol> <li>Time-calibrated trees using molecular clocks</li> <li>Identifying genomic regions under selection</li> <li>Inferring migration history</li> <li>Molecular epidemiology of viruses</li> <li>Genetic basis of tumour evolution</li> </ol> </div>
Dozent Kein Eintrag

Prabhav Kalaghatgi

Evento: eVV-Textfeld "Leitung (Publikation)" Evento: Dozierende (14 Lektionen) Lehrplanung
Dozierende in eVV
Prabhav Kalaghatgi
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Prabhav Kalaghatgi

a.SAP verarbeitet Machine Learning in Bioinformatics ( 19405701 )

Feld Evento Lehrplanung Operationen
Submodul

0262bB3.1.1

0262bB3.1.2

0262bB3.2.1

0262cB2.6.1

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0590aB1.30.1

0262bB.3.1.1

0262bB.3.1.2

0262bB.3.2.1

0262cB.2.6.1

0590aA.1.3.1

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a.Publiziert Bachelor-, Master- und Promotionskolloquium ( 19000450 )

Feld Evento Lehrplanung Operationen
Dozent

Lutz Prechelt

Kein Eintrag

a.Publiziert Begrüßungsveranstaltung für Studienanfänger der Informatik ( 19000370 )

Feld Evento Lehrplanung Operationen
Dozent Kein Eintrag

Lutz Prechelt

a.SAP verarbeitet Projektseminar zu Data Science in the Life Sciences ( 19405612 )

Feld Evento Lehrplanung Operationen
Submodul

0590aB2.1.2

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a.Absage verarbeitet Practice seminar for Phylogeny Inference and Application ( 19405502 )

Feld Evento Lehrplanung Operationen
Dozent Kein Eintrag

Prabhav Kalaghatgi

Evento: eVV-Textfeld "Leitung (Publikation)" Evento: Dozierende (14 Lektionen) Lehrplanung
Dozierende in eVV
Prabhav Kalaghatgi
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Prabhav Kalaghatgi

a.SAP verarbeitet Übung zu Machine Learning in Bioinformatics ( 19405702 )

Feld Evento Lehrplanung Operationen
Submodul

0262bB3.1.3

0262bB3.1.4

0262bB3.2.2

0262cB2.6.2

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0590aB1.30.2

0262bB.3.1.3

0262bB.3.1.4

0262bB.3.2.2

0262cB.2.6.2

0590aA.1.3.2

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a.Publiziert Mentoring für Internationale Studierende ( 19000246 )

Feld Evento Lehrplanung Operationen
Dozent Kein Eintrag

Isa Adriane Günther

Evento: eVV-Textfeld "Leitung (Publikation)" Evento: Dozierende (1 Lektionen) Lehrplanung
Dozierende in eVV
N.N.
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Noch nicht publizierte Kurse

Status LV Kursname
a.Absage verarbeitet 19402311 Reaktions-Diffusions-Simulationen für Signaltransduktionskaskaden
a.Absage verarbeitet 19405501 Phylogeny Inference and Application
a.Absage verarbeitet 19405502 Practice seminar for Phylogeny Inference and Application

In Evento fehlende Veranstaltungen

LV Kursname
19405801 Big Data Analysis in Bioinformatics

In Evento Fehlende Begleitveranstaltungen

LV Kursname
19405802 Übung zu Big Data Analysis in Bioinformatics

Im Lehrplanungssystem fehlende Veranstaltungen

Status LV Kursname