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BEGIN:VEVENT
DTSTART;TZID=UTC:20230719T140000
DTEND;TZID=UTC:20230719T190000
DTSTAMP:20260407T135729
CREATED:20230618T093724Z
LAST-MODIFIED:20230717T124306Z
UID:1330-1689775200-1689793200@isyn-mainz.de
SUMMARY:Systems Club III - Light Sheet Microscopy
DESCRIPTION:Deeper Insights: Exploring LSM in Combination with Tissue Clearing \n\n\n\n\n\nLight Sheet Microscopy (LSM) allows revolutionizing high-speed\, high-resolution imaging and reduced photo-toxicity\, proving invaluable in whole-organ and whole-organism imaging. The combined power of LSM with tissue clearing now offers unparalleled views of intact organ structures\, fostering comprehensive investigations and rich insights into the cellular landscape.The Systems Club is delighted to host an event centering on this remarkable synergy. We will explore the principles of LSM\, focusing on its feature: the illumination of thin sections of samples. A spotlight will be on tissue clearing\, a process that removes light-scattering elements from tissues\, enabling the light to penetrate deeper and offer high-throughput imaging of intact organs or organisms. \n\n\n\nThe hands-on demonstration will guide you through a typical LSM setup\, highlighting the use of tissue clearing in this context. As part of the session\, the latest software tools\, ClearMap and CellFinder\, which facilitate an unbiased\, high-throughput analysis of neuronal activity in the whole mouse brain\, will be presented. To aid those with limited programming experience\, a user-friendly graphical interface to streamline these analysis tools was developed and will be also introduced.Join us on this journey\, as we untangle the complexities of LSM and tissue clearing\, and open up new possibilities for in-depth hollistic exploration. \n\n\n\n\n\n\n\n  2 – 3:30PM: Welcome\, Presentations and Discussion Round on:    \n\n\n\n\nTissue Clearing and Light Sheet Microscopy: Implications in Neuroscience\n\n\n\nComputational Analysis of Light Sheet Microscopy data\n\n\n\n\n 3:30 – 4:30PM: Lab Tour  \n\n\n\n\nLight Sheet Microscopy and Tissue Clearing\n\n\n\n\nWhile you are waiting for your next tour slot or if you are already done\, you can start joining the catering and open discussion . \n\n\n\n 4:30PM – Open End: Discussion with Catering and Wine   \n\n\n\n \n\n\n\n Registration:  \n\n\n\nRegistration is available after login – if you do not have an ISyN-Account yet\, create one\, using the “Become a member”-Button in the top. \n\n\n\nAfter you registered for this event\, you will get an e-mail asking you for some more details regarding e.g. tours you’d like to participate in.
URL:https://isyn-mainz.de/event/systems-club-iii-light-sheet-microscopy/
LOCATION:Biozentrum 1\, Hanns-Dieter-Hüsch-Weg 15\, Mainz\, RLP\, 55128\, Germany
CATEGORIES:ISyN-Event,Systems Club
ORGANIZER;CN="Lena Fr%C3%B6hlich":MAILTO:lena.froehlich@lir-mainz.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20220729T140000
DTEND;TZID=UTC:20220729T190000
DTSTAMP:20260407T135729
CREATED:20220307T101057Z
LAST-MODIFIED:20220629T135316Z
UID:1149-1659103200-1659121200@isyn-mainz.de
SUMMARY:Systems Club II - Mouse Behavioral Tracking
DESCRIPTION:Methods for deriving Resilience against stress in mice from long term observations \n\n\n\n\n\n \n\n\n\nWhen individuals in major psychological or physical stressful situations are able to maintain their mental health or restore it quickly after a short period of experiencing stress-related symptoms\, this is referred to as resilience. The classification of mice into resilient and susceptible animals based on tests such as chronic social defeat test\, is a common approach in resilience research. However\, this classification based on short-term observation has recently been viewed increasingly critically and its transferability to the definition of resilience in humans has at least been questioned. But which methods can give us information about the long-term behavior of mice and is this really helpful for determining the resilience status of a mouse? \n\n\n\n \n\n\n\nIn our Systems Clubs we want to encourage you\, to join the discussion. Bring your own opinions and if you think it is helpful\, feel free to bring a short presentation giving a new impulse on the topic at hand. This Systems Club is particularly aimed to discover different methods for mouse behavioral tracking and to discuss them together as well as how to define resilience in general.  \n\n\n\n\n\n\n\n  2 – 3:30PM: Welcome\, Presentations and Discussion Round on:    \n\n\n\n \n\n\n\nThe IntelliCage System and Data Analysis using IntelliPy (Nicolas Ruffini)VAME\, Deeplabcut & Analysing generic tracking and behavioral data using Resilipy (Vincent Dietrich)Using and analyzing data with the LiveMouseTracker System (Saskia Göbler & Nicolas Ruffini)\n\n\n\n \n\n\n\n 3:30 – 4:30PM: Short tours showing the Live Mouse Tracker System and/or the IntelliCage System \n\n\n\n \n\n\n\nTour on the IntelliCage SystemTour on the Live Mouse Tracker System\n\n\n\n \n\n\n\n While you are waiting for your next tour slot or if you are already done\, you can start joining the catering and open discussion . \n\n\n\n 4:30PM – Open End: Discussion with Catering and Wine   \n\n\n\n \n\n\n\n\n\n Registration:  \n\n\n\n Registration is available after login – if you do not have an ISyN-Account yet\, create one\, using the “Become a member”-Button in the top. \n\n\n\n After you registered for this event\, you will get an e-mail asking you for some more details regarding e.g. tours you’d like to participate in.
URL:https://isyn-mainz.de/event/systems-club-ii-mouse-behavioral-tracking/
LOCATION:Biozentrum 1\, Hanns-Dieter-Hüsch-Weg 15\, Mainz\, RLP\, 55128\, Germany
CATEGORIES:ISyN-Event,Systems Club
ORGANIZER;CN="Nicolas Ruffini":MAILTO:nicolas.ruffini@lir-mainz.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20220527T090000
DTEND;TZID=UTC:20220527T130000
DTSTAMP:20260407T135729
CREATED:20220307T112159Z
LAST-MODIFIED:20220527T135927Z
UID:1202-1653642000-1653656400@isyn-mainz.de
SUMMARY:Deep Learning using Keras and Tensorflow
DESCRIPTION:Motivation  \n\n\n\nPython is a general-purpose\, versatile and popular programming language\, that is becoming increasingly popular in science \, for machine learning application and for general scripting and data analysis purposes. It’s great as a first language because it is concise and easy to read. However\, finding motivation to learn Python or even to consolidate learned skills after joining a workshop\, can be hard. \n\n\n\n Course Details:  \n\n\n\nThis course will be an introduction to deep learning. We will talk about different concepts\, neural network (NN) architectures and their respective implementations in Python. Concepts and algorithms are of course library independent\, nevertheless we will mainly focus on using the Keras Framework (part of Tensorflow) to implement different models. After some theoretical discussion we will setup together the deep learning environment and try to solve different problems using different NN architectures.  \n\n\n\n Requirements  \n\n\n\nYou should already feel quite comfortable in programming in python and bring some prior knowledge in how to work with pandas/numpy if possible. I would recommend to participate in the  “Scikit-Learn: Using Machine Learning in Python” courses if you are not comfortable with machine learning at all yet. I would advise to use a computer with a NVIDIA GPU to speed up computaions\, but this is not mandatory.  \n\n\n\n Correspondence:  \n\n\n\n For questions write to:  \n\n\n\nStanislav Sys – stsys@uni-mainz.de or Stephan Weißbach – s.weissbach@uni-mainz.de (regarding Content)  \n\n\n\nNicolas Ruffini Nicolas.ruffini@lir-mainz.de (regarding Event) \n\n\n\n\n\n Registration:  \n\n\n\n Registration is available after login – if you do not have an ISyN-Account yet\, create one\, using the “Become a member”-Button in the top
URL:https://isyn-mainz.de/event/deep-learning-using-keras-and-tensorflow/
LOCATION:LIR Mainz\, Wallstraße 7\, Mainz\, 55122\, Germany
CATEGORIES:ISyN-Event,Learning Python Series
ORGANIZER;CN="Nicolas Ruffini":MAILTO:nicolas.ruffini@lir-mainz.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20220520T090000
DTEND;TZID=UTC:20220520T130000
DTSTAMP:20260407T135729
CREATED:20220302T093848Z
LAST-MODIFIED:20220405T080332Z
UID:1145-1653037200-1653051600@isyn-mainz.de
SUMMARY:Scikit-Learn: Using Machine Learning in Python
DESCRIPTION:Motivation \n\n\n\nPython is a general-purpose\, versatile and popular programming language\, that is becoming increasingly popular in science \, for machine learning application and for general scripting and data analysis purposes. It’s great as a first language because it is concise and easy to read. However\, finding motivation to learn Python or even to consolidate learned skills after joining a workshop\, can be hard. \n\n\n\nThis is the third appointment out of four in our 2022 spring Python Course Series. Here we want to cover some basic machine learning techniques with the Python package scikit-learn and deepen our skills in plotting with seaborn. \n\n\n\nCourse Details: \n\n\n\nThis course will show you how to install scikit-learn on your machine and how to use some basic Machine Learning algorithms. We will talk about different concepts in Machine Learning\, about how to tackle which problems and of course also program to solve some Machine Learning problems together in Python. \n\n\n\nRequirements \n\n\n\nYou should already feel quite comfortable in programming in python and bring some prior knowledge in how to work with pandas\, the data managment library in python. If you joined the second course and were able to follow its contents\, you should also be able to follow all concepts introduced in this course- even though this time we will have to introduce some more theoretical concepts than before! \n\n\n\n \n\n\n\n \n\n\n\nCorrespondence: \n\n\n\nFor questions write to: \n\n\n\nNicolas Ruffini Nicolas.ruffini@lir-mainz.de \n\n\n\n\n\n Registration:  \n\n\n\n Registration is available after login – if you do not have an ISyN-Account yet\, create one\, using the “Become a member”-Button in the top
URL:https://isyn-mainz.de/event/scikit-learn-using-machine-learning-in-python-2/
LOCATION:LIR Mainz\, Wallstraße 7\, Mainz\, 55122\, Germany
CATEGORIES:ISyN-Event,Learning Python Series
ORGANIZER;CN="Nicolas Ruffini":MAILTO:nicolas.ruffini@lir-mainz.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20220513T090000
DTEND;TZID=UTC:20220513T130000
DTSTAMP:20260407T135729
CREATED:20220302T093325Z
LAST-MODIFIED:20220405T080242Z
UID:1143-1652432400-1652446800@isyn-mainz.de
SUMMARY:Programming and Plotting in Python for Beginners with prior knowledge
DESCRIPTION:Motivation \n\n\n\nPython is a general-purpose\, versatile and popular programming language\, that is becoming increasingly popular in science \, for machine learning application and for general scripting and data analysis purposes. It’s great as a first language because it is concise and easy to read. However\, finding motivation to learn Python or even to consolidate learned skills after joining a workshop\, can be hard. \n\n\n\nThis is the second appointment out of four in our 2022 spring Python Course Series. Here we want to cover programming in Python for users with some prior knowledge and extend the insights we got in the first course by learning the usage of some of the most useful libraries in Python for data handling and plotting. \n\n\n\nCourse Details: \n\n\n\nThis course will show you some more advanced concepts when programming with Python. We will load additional packages in Python\, and install third-party packages using pip. We will further focus on loading and working with tables using pandas and plotting with seaborn and matplotlib. \n\n\n\nRequirements \n\n\n\nSome knowledge about basic concepts of programming is helpful for this second course. \n\n\n\nFor this course\, you should already have Python installed on your machine. \n\n\n\nTry to install Python here (basic Python):https://www.python.org/downloads/ \n\n\n\nOr here (including some helpful packages and package managing):https://www.anaconda.com/products/individual \n\n\n\nYou can also start getting familiar with Python\, e.g. using one of these online courses:https://www.datacamp.com/courses/intro-to-python-for-data-sciencehttps://www.codecademy.com/learn/learn-python-3 \n\n\n\nCorrespondence: \n\n\n\nFor questions write to: \n\n\n\nNicolas Ruffini Nicolas.ruffini@lir-mainz.de \n\n\n\n \n\n\n\n\n\n Registration:  \n\n\n\n Registration is available after login – if you do not have an ISyN-Account yet\, create one\, using the “Become a member”-Button in the top
URL:https://isyn-mainz.de/event/programming-and-plotting-in-python-for-beginners-with-prior-knowledge-2/
LOCATION:LIR Mainz\, Wallstraße 7\, Mainz\, 55122\, Germany
CATEGORIES:ISyN-Event,Learning Python Series
ORGANIZER;CN="Nicolas Ruffini":MAILTO:nicolas.ruffini@lir-mainz.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20220506T090000
DTEND;TZID=UTC:20220506T130000
DTSTAMP:20260407T135729
CREATED:20220302T092945Z
LAST-MODIFIED:20220405T080215Z
UID:1134-1651827600-1651842000@isyn-mainz.de
SUMMARY:Python for total Beginners
DESCRIPTION:Motivation \n\n\n\nPython is a general-purpose\, versatile and popular programming language\, that is becoming increasingly popular in science \, for machine learning application and for general scripting and data analysis purposes. It’s great as a first language because it is concise and easy to read. However\, finding motivation to learn Python or even to consolidate learned skills after joining a workshop\, can be hard. \n\n\n\nThus\, we want to offer a weekly Hands-On programming course in Python\, to start with basic programming concepts for total beginners and then tackle more advanced topics in the following three appointments. \n\n\n\nCourse Details: \n\n\n\nThis course will show you how to install Python on your machine and together we aim to understand the basic concepts of programming in Python. We will have a look into some basic objects in programming such as integers\, floats\, strings and will cover some concepts such as loops and if-else conditions. \n\n\n\nRequirements \n\n\n\nNo deeper knowledge about programming is necessary for the first course. If you have some preferences and / or  are already familiar with some concepts  of Python or programming in general\, join form the second/ third/ fourth course on\, or just tell us\, so we can shift our focus if many of you are interested in a specific topic. \n\n\n\nIf you already want to prepare some more\, try to install Python here (basic Python):https://www.python.org/downloads/ \n\n\n\nOr here (including some helpful packages and package managing):https://www.anaconda.com/products/individual \n\n\n\nYou can also start getting familiar with Python\, e.g. using one of these online courses:https://www.datacamp.com/courses/intro-to-python-for-data-sciencehttps://www.codecademy.com/learn/learn-python-3 \n\n\n\nCorrespondence: \n\n\n\nFor questions write to: \n\n\n\nNicolas Ruffini Nicolas.ruffini@lir-mainz.de \n\n\n\n\n\n Registration:  \n\n\n\n Registration is available after login – if you do not have an ISyN-Account yet\, create one\, using the “Become a member”-Button in the top
URL:https://isyn-mainz.de/event/python-for-total-beginners-2/
LOCATION:LIR Mainz\, Wallstraße 7\, Mainz\, 55122\, Germany
CATEGORIES:ISyN-Event,Learning Python Series
ORGANIZER;CN="Nicolas Ruffini":MAILTO:nicolas.ruffini@lir-mainz.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20220429T140000
DTEND;TZID=UTC:20220429T190000
DTSTAMP:20260407T135729
CREATED:20220307T101055Z
LAST-MODIFIED:20220405T075904Z
UID:1132-1651240800-1651258800@isyn-mainz.de
SUMMARY:Systems Club I - Calcium Imaging Pipeline:
DESCRIPTION:From Data Acquisition to Analysis \n\n\n\n\n\nThe field of optical calcium imaging\, particularly of individual neuron function in the intact tissue\, relies on detecting subtle changes in light intensity. The implementation of 2-photon microscopy in combination with calcium indicators allowed for the first time a functional readout of neuronal circuits comprising of several hundred neurons in the rodent cortex. This led to a tremendous advance in our understanding on how complex circuit dysfunction arise\, particularly also in early stages of neurological disorders. Particularly 2 photon calcium imaging approaches pose unique challenges\, both in terms of system integration\, experimental design\, and not the least\, analysis. Most of these steps are processed quite differently depending on the laboratory. Here\, in a hands-on-manner\, we aim to show you our procedure of data acquisition and analysis\, including the GUI ViNe-Seg\, which has been recently developed in the Stroh-Lab. \n\n\n\nIn our Systems Clubs we want to encourage you to join the discussion. Bring your own opinions and if you think it is helpful\, feel free to bring a short presentation giving a new impulse on the topic at hand. This Systems Club is particularly aiming for initiating a discussion of different procedures for image processing and downstream analyses of calcium imaging data. \n\n\n\n\n\n\n\n The planned time table is the following:  \n\n\n\n 2 – 3:30PM: Welcome\, Presentations and Discussion Round on:   \n\n\n\n \n\n\n\nThe Data Acquisition (Hendrik Backhaus)The Autosegmentation\, Trace Extraction\, Baseline Estimation and Peak Detection (Nicolas Ruffini\, Saleh Altahini\, Hendrik Backhaus)The Downstream Analysis (Anna Wierczeiko\, Nicolas Ruffini)\n\n\n\n \n\n\n\n 3:30 – 4:30PM: Short tours showing the Experimental Calcium Imaging Setup in RG Stroh  \n\n\n\n \n\n\n\n2-Photon Microscope TourMiniscope & Electrophysiology Tour\n\n\n\n \n\n\n\nWhile you are waiting for your next tour slot or if you are already done\, you can start joining the catering and open discussion. \n\n\n\n 4:30PM – Open End: Discussion with Catering and Wine  \n\n\n\n \n\n\n\nRegistration: \n\n\n\nRegistration is available after login – if you do not have an ISyN-Account yet\, create one\, using the “Become a member”-Button in the top \n\n\n\nAfter you registered for this event\, you will get an e-mail asking you for some more details regarding e.g. tours you’d like to participate in.
URL:https://isyn-mainz.de/event/systems-club-i-calcium-imaging-pipeline/
LOCATION:Biozentrum 1\, Hanns-Dieter-Hüsch-Weg 15\, Mainz\, RLP\, 55128\, Germany
CATEGORIES:ISyN-Event,Systems Club
ORGANIZER;CN="Nicolas Ruffini":MAILTO:nicolas.ruffini@lir-mainz.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20211203T090000
DTEND;TZID=UTC:20211203T130000
DTSTAMP:20260407T135729
CREATED:20211002T135905Z
LAST-MODIFIED:20211004T145956Z
UID:1082-1638522000-1638536400@isyn-mainz.de
SUMMARY:Scikit-Learn: Using Machine Learning in Python
DESCRIPTION:Motivation \nPython is a general-purpose\, versatile and popular programming language\, that is becoming increasingly popular in science \, for machine learning application and for general scripting and data analysis purposes. It’s great as a first language because it is concise and easy to read. However\, finding motivation to learn Python or even to consolidate learned skills after joining a workshop\, can be hard. \nThus\, we want to offer a biweekly Hands-On programming course in Python\, to start with basic programming concepts for total beginners and then tackle more advanced topics in the following three appointments. \nCourse Details: \nThis course will show you how to install scikit-learn on your machine and how to use some basic Machine Learning algorithms. We will talk about different concepts in Machine Learning\, about how to tackle which problems and of course also program to solve some Machine Learning problems together in Python. \nRequirements \nNo deeper knowledge about programming is necessary for the first course. If you have some preferences and / or  are already familiar with some concepts  of Python or programming in general\, join form the second/ third/ fourth course on\, or just tell us\, so we can shift our focus if many of you are interested in a specific topic. \nIf you already want to prepare some more\, try to install Python here:\nhttps://www.python.org/downloads/ \nYou can also start getting familiar with Python\, e.g. using one of these online courses:\nhttps://www.datacamp.com/courses/intro-to-python-for-data-science\nhttps://www.codecademy.com/learn/learn-python-3 \nCorrespondence: \nFor questions write to: \nRoberta Guimaraes-Backhaus Roberta.Backhaus@lir-mainz.de  or \nNicolas Ruffini Nicolas.ruffini@lir-mainz.de
URL:https://isyn-mainz.de/event/scikit-learn-using-machine-learning-in-python/
LOCATION:RLP
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20211105T090000
DTEND;TZID=UTC:20211126T130000
DTSTAMP:20260407T135729
CREATED:20211002T135504Z
LAST-MODIFIED:20211021T073653Z
UID:1078-1636102800-1637931600@isyn-mainz.de
SUMMARY:Programming and Plotting in Python for Beginners with prior knowledge
DESCRIPTION:Offline course for four groups\, each at one friday in november. \n\n\n\n\n	Motivation \nPython is a general-purpose\, versatile and popular programming language\, that is becoming increasingly popular in science \, for machine learning application and for general scripting and data analysis purposes. It’s great as a first language because it is concise and easy to read. However\, finding motivation to learn Python or even to consolidate learned skills after joining a workshop\, can be hard. \nAs we had more registrations than we could handle for the advanced programming course and no registrations were made for plotting only\, we decided to separate all registrations into four groups instead of two groups. Consequently\, we can arrange four appointments with each approx. ten participants in november for learning both\, programming in Python for users with some prior knowledge and usage of some of the most useful libraries in Python for data handling and plotting. \nCourse Details: \nThis course will show you some more advanced concepts when programming with Python. We will load additional packages in Python\, and install third-party packages using pip. We will further focus on loading and working with tables using pandas and plotting with seaborn and matplotlib. \nRequirements \nSome knowledge about basic concepts of programming is helpful for this second course. \nFor this course\, you should already have Python installed on your machine. \nTry to install Python here (basic Python):\nhttps://www.python.org/downloads/ \nOr here (including some helpful packages and package managing):\nhttps://www.anaconda.com/products/individual \nYou can also start getting familiar with Python\, e.g. using one of these online courses:\nhttps://www.datacamp.com/courses/intro-to-python-for-data-science\nhttps://www.codecademy.com/learn/learn-python-3 \nCorrespondence: \nFor questions write to: \nNicolas Ruffini Nicolas.ruffini@lir-mainz.de
URL:https://isyn-mainz.de/event/programming-and-plotting-in-python-for-beginners-with-prior-knowledge/
LOCATION:RLP
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20211022T090000
DTEND;TZID=UTC:20211022T130000
DTSTAMP:20260407T135729
CREATED:20211002T135309Z
LAST-MODIFIED:20211021T080800Z
UID:1074-1634893200-1634907600@isyn-mainz.de
SUMMARY:Python for total Beginners
DESCRIPTION:Registration Closed\nMotivation \nPython is a general-purpose\, versatile and popular programming language\, that is becoming increasingly popular in science \, for machine learning application and for general scripting and data analysis purposes. It’s great as a first language because it is concise and easy to read. However\, finding motivation to learn Python or even to consolidate learned skills after joining a workshop\, can be hard. \nThus\, we want to offer a biweekly Hands-On programming course in Python\, to start with basic programming concepts for total beginners and then tackle more advanced topics in the following three appointments. \nCourse Details: \nThis course will show you how to install Python on your machine and together we aim to understand the basic concepts of programming in Python. No deeper knowledge about programming is necessary for this first course. If you have some preferences and / or  are already familiar with some concepts  of Python or programming in general\, join form the second/ third/ fourth course on. \nRequirements \nNo deeper knowledge about programming is necessary for the first course. If you have some preferences and / or  are already familiar with some concepts  of Python or programming in general\, join form the second/ third/ fourth course on\, or just tell us\, so we can shift our focus if many of you are interested in a specific topic. \nIf you already want to prepare some more\, try to install Python here (basic Python):\nhttps://www.python.org/downloads/ \nOr here (including some helpful packages and package managing):\nhttps://www.anaconda.com/products/individual \nYou can also start getting familiar with Python\, e.g. using one of these online courses:\nhttps://www.datacamp.com/courses/intro-to-python-for-data-science\nhttps://www.codecademy.com/learn/learn-python-3 \nCorrespondence: \nFor questions write to: \nNicolas Ruffini Nicolas.ruffini@lir-mainz.de
URL:https://isyn-mainz.de/event/python-for-total-beginners/
LOCATION:RLP
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210629T080000
DTEND;TZID=UTC:20210629T170000
DTSTAMP:20260407T135729
CREATED:20201116T161146Z
LAST-MODIFIED:20210324T174752Z
UID:524-1624953600-1624986000@isyn-mainz.de
SUMMARY:Hands-on Programming - Introduction to Python
DESCRIPTION:Motivation\nPython is a general-purpose\, versatile and popular programming language.Python is becoming increasingly popular in science \, for machine learning application and for general scripting and data analysis purposes. It’s great as a first language because it is concise and easy to read. \nOutline\nIn this Hands-On Tutorial\, I will try to get you familiar with the Installation\, Usage and the benefits of the Python Programming language. Depending on your own skill set and interests\, we can dive deeper into the pandas module for Data Science\, SciKitLearn for some basic Machine Learning or just get familiar with the general properties of Python. \nRequirements\nNo deeper knowledge about programming is necessary. If you have some preferences and / or  are already familiar with some concepts  of Python or programming in general\, tell me\, so I can try to prepare the course accordingly. \nIf you already want to prepare some more\, try to install Python here:\nhttps://www.python.org/downloads/ \nYou can also start getting familiar with Python\, e.g. using one of these online courses:\nhttps://www.datacamp.com/courses/intro-to-python-for-data-science\nhttps://www.codecademy.com/learn/learn-python-3 \nCorrespondence:\nFor questions write to: Nicolas.ruffini@lir-mainz.de
URL:https://isyn-mainz.de/event/hands-on-programming-introduction-to-python/
LOCATION:RLP
CATEGORIES:ISyN-Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20210621T080000
DTEND;TZID=UTC:20210621T170000
DTSTAMP:20260407T135729
CREATED:20201116T160429Z
LAST-MODIFIED:20210324T174810Z
UID:522-1624262400-1624294800@isyn-mainz.de
SUMMARY:Hands-on Data Analysis: IntelliPy
DESCRIPTION:Python GUI for analyzing IntelliCage data\nMotivation\nThe IntelliCage system helps researchers to conduct behavioral experiments and learning experiments with mice while ensuring minimal human intervention. The animals can be observed for long time periods – up to several weeks. This long-term data acquisition can provide new insights in mouse behavior\, that might not be detectable in short-term observations. However\, analyzing those big amounts of data is challenging for many researchers. \nIntelliPy aims to simplify and automize many aspects of the analysis\, such as acquiring data per group\, creating learning curves or pivoting parameters in different timeframes. All plots are automatically created and the final tables for statistical tests are stored separately for the user. \n \nOutline\nIn this Hands-On Tutorial\, I will try to get you familiar with the Installation\, Usage and the benefits of the IntelliPy GUI. \nRequirements\nNo deeper knowledge about programming is necessary\, as IntelliPy is aimed to be useable by scientists with little or no programming / data science experience. \nDetails\nIntelliPy is capable of doing three kind of analyses: \n\nPivot Analyses\nLearning Analyses\nSucrose Analyses\n\nPivot Analyses:\nFor the parameters\, measured by the IntelliCage Systems\, such as Lick Duration\, Nosepoke Number or NosepokeDuration\, pivot tables are created for each module by IntelliPy. By default\, these timeframes are created per day\, but the user can add more timeframes using the IntelliPy GUI\, like e.g. 12-hour or 6-hour timeframes. For further sttistical analyses\, the pivoting results are stored as CSV files. \nLearning Analyses:\nAs the experiments conducted with the IntelliCage systems can be conducted as learning experiments with different setups per phase\, the learning rate of each individual as well as for the each group can be of high interest. Rather than only the final rate of correct attempts\, the rate per hour and per visit is computed and plotted by IntelliPy. This enables the user\, to utilize longitudinal learning information for each individual and group. For those learning rates\, it is even possible to include all nosepokes or to remove those that were not followed by a lick. It can be argued about\, whether a nosepoe without a lick should or shouldn’t be accounted as a correct attempt\, so this decision is up to the user. Furthermoe\, there are both\, the possibility to exclude all nosepokes not followed by a lick or to treat them as incorrect attempts. \nSucrose Analyses:\nFor learning experiments\, including the choice between water and sucrose\, the proportion of LickDuration spent for Sucrose over time is computed by IntelliPy. Additionally\, it is possible to define Sucrose and Water or just one of both as correct for the learning rate. \nCorrespondence:\nFor questions write to: Nicolas.ruffini@lir-mainz.de
URL:https://isyn-mainz.de/event/hands-on-data-analysis-intellipy/
LOCATION:RLP
CATEGORIES:ISyN-Event
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