BEGIN:VCALENDAR VERSION:2.0 PRODID:-//PR Stats - ECPv6.15.20//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:PR Stats X-ORIGINAL-URL:https://prstats.org X-WR-CALDESC:Events for PR Stats REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:Europe/London BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20250330T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20251026T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20260329T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20261025T010000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:+0000 TZOFFSETTO:+0100 TZNAME:BST DTSTART:20270328T010000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:+0100 TZOFFSETTO:+0000 TZNAME:GMT DTSTART:20271031T010000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;VALUE=DATE:20260601 DTEND;VALUE=DATE:20260604 DTSTAMP:20260418T062503 CREATED:20260130T151942Z LAST-MODIFIED:20260311T161505Z UID:10000587-1780272000-1780531199@prstats.org SUMMARY:Species Distribution Modelling With Bayesian Statistics (SDMB08) DESCRIPTION:Joint Species Distribution Modelling (JSDM) using HMSC: A Hierarchical Modelling Approach (JSDM01)\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Event Date \nTuesday\, September 30th\, 2025\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees\nthrough the accompanying computer practicals via video link\, so a good internet connection is\nessential. \nTime Zone\nTIME ZONE – Portugal (GMT+1) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you.\n \n \n \n \n \n \n \n \n \n \n About This Course\n This course focuses on the use of BART (Bayesian Additive Regression Trees) for modelling\nspecies’ geographical distributions based on occurrence data and environmental variables. BART is a relatively recent technique that shows very promising results in the field of species distribution and ecological niche modelling (SDM / ENM)\, as it produces accurate predictions (considering various aspects of model performance) without overfitting to noise or to special cases in the data. Additionally\, BART allows mapping the uncertainty and credible intervals associated to each local prediction. \nThe course includes a combination of theoretical lectures and hands-on practicals in R\, as well as\nopen discussions about models and data for SDM applications. The practicals go through a\ncomplete worked example\, from data preparation to model output analysis\, with annotated R\nscripts that can be adapted on-the-spot by participants to work on their own species of interest.\nAlong the course\, the instructor is available for constant feedback and orientation on participants’; outputs and interpretations.\n \n \n \n \n \n Intended Audiences\n The course is aimed at students\, researchers and practitioners with an interest in implementing\nbest practices and state-of-the-art methods for modelling species’ distributions or ecological\nniches\, in an automated and reproducible way.\n \n \n \n \n \n Venue\n Delivered remotely\n \n \n \n \n \n Course Details\n Availability – 18 places \nDuration – 3 days \nContact hours – Approx. 12 hours live\, plus remote assistance via Slack from the first day to the\nweekday after the course. \nECT’s – Equal to 1.5 ECT’s \nLanguage – English\n \n \n \n \n \n Teaching Format\n This course runs along 3 days\, each with a 4-hour live online session. Each session is divided into\n4 parts\, alternating between theoretical lectures and hands-on practicals. Annotated scripts are\nprovided and instructor assistance is available\, both during the live sessions (on Zoom) and\nwhenever possible the rest of the day (on Slack)\, until the weekday after the course.\nLive sessions will be video-recorded\, uploaded to a video hosting website as soon as possible after\neach session\, and remain available for one month after the course.\n \n \n \n \n \n Assumed quantitative knowledge\n Participants should know what species distribution or ecological niche models (SDM / ENM) are\,\nand ideally have some previous experience with the basics. Previous knowledge of Bayesian\nstatistics is not required.\n \n \n \n \n \n Assumed computer background\n Participants should have some previous experience with R\, including package installation and\nbasic data handling\, although commented scripts will be provided for the entire course.\n \n \n \n \n \n Equipment and software requirements\n \nParticipants must use a computer with a good internet connection\, a working recent version or R (and ideally also RStudio)\, and recent versions of some R packages whose installation instructions will be sent a few days before the course. A working webcam is desirable for enhanced interactivity during the live sessions. Some computation power is required for modelling large datasets\, although the provided example data (and suggested subsets of participants’ data) can run on an ordinary laptop. \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Tickets \n \n \n \n \n \n \n The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities. \n\n\n\n \n \n HMSC01 ONLINE\n \n HMSC01 ONLINE\n\n \n \n \n \n £\n 450.00\n \n \n\n \n Unlimited \n \n \n Open the ticket description.\n More \n \n Close the ticket description.\n Less \n \n \n\n \n \n Decrease ticket quantity for HMSC01 ONLINE\n -\n \n \n Quantity \n \n\n \n Increase ticket quantity for HMSC01 ONLINE\n +\n \n \n \n \n\n \n \n Quantity: \n 0\n\n \n \n Total: \n \n \n \n £\n 0.00\n \n \n\n \n Get Tickets\n \n\n \n \n \n\n \n \n\n \n \n\n \n\n\n\n\n\n \n\n\n \n \n \n \n \n \n \n \n \n \n \n PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n \n \n \n \n \n \nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n COURSE PROGRAMME\n \n \n \n \n \n \n \n \n \n \n Tuesday 30th\n Day 1 – Classes from 14:00 –  18:00 \n\nModule 1a: Obtain and process data\, including species presences and environmental variables\nPractical\nModule 1b: Determine an adequate spatial resolution and extent for modelling\nPractical\n\n \n \n \n \n \n Wednesday 1st\n Day 2 – Classes from 14:00 –  18:00 \n\nModule 2a: Build a species distribution model with BART and obtain predictions of environmental favorability\, with credibility intervals and associated uncertainty\nPractical\nModule 2b: Evaluate and cross-validate the model\, assessing various aspects of predictive ability\nPractical\n\n \n \n \n \n \n \n Thursday 2nd\n Day 3 – Classes from 14:00 –  18:00 \n\n Module 3a: Quantify variable contributions and try out different methods for selecting relevant variables\nPractical\nModule 3b: Plot and map the species’ partial response to each variable\nPractical\n\n \n \n \n \n \n \n \n \n Dr. Marcia Barbosa\n \n Márcia is an experienced researcher and instructor in biogeography and macroecology\, particularly in geographic information systems and species distribution modelling. She’s also a reviewer and editor for scientific journals and funding agencies\, and a promoter and developer of free and open-source software implementing transparency\, reproducibility and best practices. You can see her publication list at her website or at Publons/ResearcherID\, Scopus\, ORCID\, Google Scholar\, or ResearchGate. \nResearch Gate \nGoogle Scholar \nORCID \nGitHub \nHomepage URL:https://prstats.org/course/species-distribution-modelling-with-bayesian-statistics-sdmb08/ LOCATION:Delivered remotely (United Kingdom)\, Western European Time Zone\, United Kingdom CATEGORIES:All Live Courses,Home Courses,Live Online Courses ATTACH;FMTTYPE=image/jpeg:https://prstats.org/wp-content/uploads/2024/06/SDMB07-1.jpg GEO:53.1423672;-7.6920536 END:VEVENT BEGIN:VEVENT DTSTART;VALUE=DATE:20260601 DTEND;VALUE=DATE:20260606 DTSTAMP:20260418T062503 CREATED:20260114T153444Z LAST-MODIFIED:20260114T153454Z UID:10000581-1780272000-1780703999@prstats.org SUMMARY:Introduction to Processing and Analysis of Spatial Multiplexed Proteomics Data (SPMP02) DESCRIPTION:Joint Species Distribution Modelling (JSDM) using HMSC: A Hierarchical Modelling Approach (JSDM01)\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Event Date \nMonday\, October 6th\, 2025\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Course Format\nThis is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link\, a good internet connection is essential. \nTime Zone\nTIME ZONE – UK (GMT) local time – however all sessions will be recorded and made available allowing attendees from different time zones to follow. \nPlease email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you.\n \n \n \n \n \n \n \n \n \n \n About this course\n The study of animal acoustic signals is a central tool for many fields in behavior\, ecology\, evolution and biodiversity monitoring. The accessibility of recording equipment and growing availability of open-access acoustic libraries provide an unprecedented opportunity to study animal acoustic signals at large temporal\, geographic and taxonomic scales. However\, the diversity of analytical methods and the multidimensionality of these signals posts significant challenges to conduct analyses that can quantify biologically meaningful variation. The recent development of acoustic analysis tools in the R programming environment provides a powerful means for overcoming these challenges\, facilitating the gathering and organization of large acoustic data sets and the use of more elaborated analyses that better fit the studied acoustic signals and associated biological questions. The course will introduce students on the basic concepts in animal acoustic signal research as well as hands-on experience on analytical tools in R. \nBy the end of the course\, participants should be able to: \n\nUnderstand the basic concepts of bioacoustics and how animal acoustic signals are analyzed\nGain proficiency in handling and manipulating acoustic data in R\, including working with ‘wave’ objects and other audio formats\nDevelop skills in building and interpreting spectrograms using Fourier transform techniques and the seewave package in R\nImport Raven Pro annotations into R and refine these annotations with warbleR functions\nUnderstand how to quantify the structure of acoustic signals through various approaches\nGain experience in quality control of recordings and annotations\, ensuring data integrity and accuracy\nCompare different methods for quantifying acoustic signal structure and understand the implications of each approach\n\n \n \n \n \n \n Intended Audiences\n \nAcademics and post-graduate students conducting research in bioacoustics\, animal behavior\, ecology\, or related fields\nApplied researchers and analysts in public\, private\, or non-profit organizations who require robust\, reproducible\, and flexible tools for analyzing acoustic data\nCurrent R users seeking to expand their knowledge into the field of bioacoustics and learn how to utilize specialized packages for acoustic analysis\nWildlife biologists\, and conservationists interested in leveraging bioacoustic methods for species monitoring and behavioral studies\nData scientists and programmers interested in applying their coding skills to the analysis of animal acoustic signals\n\n \n \n \n \n \n Venue\n Delivered remotely\n \n \n \n \n \n Course Details\n Time Zone – UK (GMT) local time \nAvailability – 20 places \nDuration – 5 days\, 4 hours per day \nContact hours – Approx. 20 hours \nECT’s – Equal to 2 ECT’s \nLanguage – English\n \n \n \n \n \n Teaching Format\n Introductory lectures on the concepts and refreshers on R usage. Intermediate-level lectures interspersed with hands-on mini practicals and longer projects. Data sets for computer practicals will be provided by the instructors\, but participants are welcome to bring their own data. \n\n \n \n \n \n \n Assumed quantitative knowledge\n A basic understanding of statistical concepts. Specifically\, generalised linear regression models\, statistical significance\, hypothesis testing.\n \n \n \n \n \n Assumed computer background\n Familiarity with R. Ability to import/export data\, manipulate data frames\, fit basic statistical models & generate simple exploratory and diagnostic plots.\n \n \n \n \n \n Equipment and software requirements\n \nA laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs\, Macs\, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/. \n\n\nAll the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed\, and a full list of required packages will be made available to all attendees prior to the course. \n\n\nA working webcam is desirable for enhanced interactivity during the live sessions\, we encourage attendees to keep their cameras on during live zoom sessions. \n\n\nAlthough not strictly required\, using a large monitor or preferably even a second monitor will improve he learning experience \n\n\nDownload R \n\n\nDownload RStudio \n\n\nDownload Zoom \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Tickets \n \n \n \n \n \n \n The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities. \n\n\n\n \n \n HMSC01 ONLINE\n \n HMSC01 ONLINE\n\n \n \n \n \n £\n 450.00\n \n \n\n \n Unlimited \n \n \n Open the ticket description.\n More \n \n Close the ticket description.\n Less \n \n \n\n \n \n Decrease ticket quantity for HMSC01 ONLINE\n -\n \n \n Quantity \n \n\n \n Increase ticket quantity for HMSC01 ONLINE\n +\n \n \n \n \n\n \n \n Quantity: \n 0\n\n \n \n Total: \n \n \n \n £\n 0.00\n \n \n\n \n Get Tickets\n \n\n \n \n \n\n \n \n\n \n \n\n \n\n\n\n\n\n \n\n\n \n \n \n \n \n \n \n \n \n \n \n PLEASE READ – CANCELLATION POLICY \nCancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered\, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.\n \n \n \n \n \n \n\n\nIf you are unsure about course suitability\, please get in touch by email to find out more oliverhooker@prstatistics.com \n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Course Programme\n \n \n \n \n \n \n \n \n \n \n Monday 6th\n Day 1 – Classes from 13:30 – 17:30 \nIntroduction \n\nHow animal acoustic signals look like?\nAn overview of the variety of acoustic signals produced by animals\, with examples from different species. This includes visualizing sound waves and spectrograms to understand their structure and complexity.\nAnalytical workflow in bioacoustics research\nIntroduction to the step-by-step process involved in bioacoustic research\, from recording and\ndata collection to analysis and interpretation. This session will outline the typical workflow\,\nemphasizing the importance of each step.\nAdvantages of programming\nDiscussion on the benefits of using programming languages like R for bioacoustic analysis\,\nincluding reproducibility\, efficiency\, and the ability to handle large datasets. This will highlight\nhow programming can enhance research capabilities.\n\n  \nWhat is sound? \n\nSound as a time series\nExplanation of how sound can be represented as a time series\, with each point in the series\nrepresenting the sound pressure level at a given moment in time. This forms the basis for further analysis and manipulation.\nSound as a digital object\nDiscussion on the digitization of sound\, including sampling rates\, bit depth\, and the conversion of analog sound waves into digital formats that can be analyzed using software.\nAcoustic data in R\nIntroduction to handling and analyzing acoustic data in R. This includes importing sound files\, basic data exploration\, and visualization techniques.\n‘wave’ object structure\nExplanation of the ‘wave’ object in R\, its structure\, and the information it contains. This is\nessential for understanding how to manipulate and analyze sound data in R.\n‘wave’ object manipulations\nTechniques for manipulating ‘wave’ objects\, including trimming\, concatenating\, and modifying sound files. Practical exercises will be provided to reinforce these concepts.\nAdditional formats\nOverview of other audio file formats (e.g.\, MP3\, FLAC) and how they can be converted and used in R for bioacoustic analysis.\n\n \n \n \n \n \n Tuesday 7th\n Day 2 – Classes from 13:30 – 17:30 \nBuilding spectrograms \n\nFourier transform\nExplanation of the Fourier transform and its application in converting time-domain signals into\nfrequency-domain representations. This is the foundation for creating spectrograms.\nBuilding a spectrogram\nStep-by-step guide on how to construct spectrograms\, including parameter selection (e.g.\,\nwindow size\, overlap) and interpretation of the resulting visual representations.\nCharacteristics and limitations\nDiscussion on the strengths and limitations of spectrograms\, including resolution trade-offs and potential artifacts. Participants will learn to critically evaluate spectrograms.\nSpectrograms in R\nPractical session on generating and customizing spectrograms in R using the seewave package.\nParticipants will create spectrograms from their own data.\nPackage seewave\nExplore\, modify and measure ‘wave’ objects\nHands-on exploration of the seewave package\, focusing on functions for modifying and\nmeasuring 'wave' objects. This includes exercises on filtering\, re-sampling\, and extracting acoustic features.\nSpectrograms and oscillograms\nCreating and interpreting both spectrograms and oscillograms in R. Participants will learn to\nvisualize sound data in different ways to highlight various aspects of the signal.\nFiltering and re-sampling\nTechniques for filtering (e.g.\, band-pass\, high-pass) and re-sampling sound files to focus on\nspecific frequency ranges or standardize sampling rates.\nAcoustic measurements\nUsing the seewave package to perform detailed acoustic measurements\, such as peak frequency\, dominant frequency\, and frequency range. Practical examples will be provided.\n\n \n \n \n \n \n Wednesday 8th\n Day 3 – Classes from 13:30 – 17:30 \nAnnotations \n\nIntroduction to the Raven Pro Interface\nA guided tour of the Raven Pro software\, its main features\, and interface elements. Participants will learn how to navigate the software efficiently.\nIntroduction to selections and measurements\nInstruction on how to make selections within sound files and take basic measurements such as duration and frequency using Raven Pro.\nSaving\, retrieving\, and exporting selection tables\nHow to save\, retrieve\, and export selection tables in Raven Pro for further analysis. This session will cover best practices for data management and organization.\nUsing annotations\nTechniques for annotating sound files in Raven Pro\, including the use of labels and notes to mark significant events or features within the recordings.\n\n  \nQuantifying acoustic signal structure \n\nSpectro-temporal measurements (spectro_analysis())\nIntroduction to the spectro_analysis() function in R for extracting spectro-temporal\nmeasurements from audio recordings. Participants will learn to describe acoustic signals in terms of their temporal and spectral characteristics.\nParameter description\nDetailed explanation of key acoustic parameters\, such as duration\, frequency range\, and\namplitude\, and how they are used to describe sound signals.\nHarmonic content\nTechniques for analyzing the harmonic content of signals\, including identifying harmonic series and measuring harmonic-to-noise ratios.\nCepstral coefficients (mfcc_stats())\nIntroduction to Mel-frequency cepstral coefficients (MFCCs) and their use in characterizing the timbral properties of sound signals. Participants will use the mfcc_stats() function to extract MFCCs.\nCross-correlation (cross_correlation())\nExplanation of cross-correlation techniques for comparing sound signals. Participants will use cross_correlation() to measure the similarity between different recordings.\nDynamic time warping (freq_DTW())\nIntroduction to dynamic time warping (DTW) and its application in aligning and comparing time-series data. The freq_DTW() function will be used to compare sound signals.\nSignal-to-noise ratio (sig2noise())\nTechniques for calculating the signal-to-noise ratio (SNR) of recordings\, which is crucial for\nassessing the quality of sound data.\nInflections (inflections())\nIdentifying and measuring inflections in sound signals\, which can indicate changes in pitch or other dynamic features.\nParameters at other levels (song_analysis())\nExploring acoustic parameters at higher hierarchical levels\, such as entire songs or sequences of vocalizations\, using the song_analysis() function.\n\n \n \n \n \n \n Thursday 9th\n Day 4 – Classes from 13:30 – 17:30 \nQuality control in recordings and annotations \n\nCreate catalogs\nCompiling catalogs of annotated sound files\, which can be used for further analysis or as\nreference materials.\nCheck and modify sound file format (check_wavs()\, info_wavs()\, duration_wavs()\,\nmp32wav() y fix_wavs())\nTechniques for checking and modifying sound file formats using various functions in R. This\nincludes converting files\, checking file integrity\, and fixing common issues.\nTuning spectrogram parameters (tweak_spectro())\nAdjusting spectrogram parameters to optimize the visualization and analysis of sound signals.\nParticipants will use tweak_spectro() to fine-tune their spectrograms.\nDouble-checking selection tables (check_sels()\, spectrograms()\, full_spectrograms() &\ncatalog())\nMethods for verifying and refining selection tables\, ensuring that all annotations are accurate and comprehensive.\nRe-adjusting selections (tailor_sels())\nTechniques for re-adjusting selections in response to quality control checks\, ensuring that all\nannotations are precise and correctly positioned.\nCharacterizing hierarchical levels in acoustic signals\nCreating ‘song’ spectrograms (full_spectrograms()\, spectrograms())\nBuilding spectrograms that represent entire songs or sequences of vocalizations\, providing a\nhigher-level view of acoustic patterns.\n‘Song’ parameters (song_analysis())\nMeasuring and analyzing parameters at the song level\, such as song duration\, number of\nelements and element rate\, using the song_analysis() function.\n\n \n \n \n \n \n Friday 10th\n Day 5 – Classes from 13:30 – 17:30 \nChoosing the right method for quantifying structure \n\nCompare different methods for quantifying structure (compare_methods())\nComparing various methods for quantifying acoustic signal structure. Participants will use\ncompare_methods() to evaluate different approaches.\nQuantifying acoustic spaces\nIntro to PhenotypeSpace\nIntroduction to the concept of acoustic spaces and the PhenotypeSpace framework\, which allows for the visualization and comparison of acoustic diversity.\nQuantifying space size\nTechniques for measuring the size of acoustic spaces\, which can provide insights into the\nvariability and complexity of vocalizations.\nComparing sub-spaces\nMethods for comparing different sub-spaces within the overall acoustic space\, allowing for the analysis of variations between species\, populations\, or other groups.\nEach of these topics will be covered with detailed explanations\, practical examples\, and hands-on exercises to ensure that participants gain a comprehensive understanding of bioacoustics research using the R platform.\n\n \n \n \n \n \n \n Course Instructor\n \n*\nDr. Marcelo Araya Salas\nWorks at – Neuroscience Research Center\, Universidad de Costa Rica \nMarcelo Araya-Salas works at the intersection of scientific programming and evolutionary behavioral ecology\, focusing on the evolution of behavior and the factors influencing it across cultural and evolutionary timescales. His research primarily examines the communication systems of neotropical species using single-species behavioral studies\, comparative phylogenetic methods\, and advanced data analysis techniques. He has developed several computational tools for biological data analysis\, including the R packages warbleR\, Rraven and baRulho which simplify the manipulation of annotated acoustic data and the quantification of structure and degradation of animal sounds. \nResearchGate \nGoogle Scholar \nWork Homepage \nPersonal Homepage URL:https://prstats.org/course/introduction-to-processing-and-analysis-of-spatial-multiplexed-proteomics-data-spmp02/ LOCATION:Delivered remotely (United Kingdom)\, Western European Time\, United Kingdom CATEGORIES:All Live Courses,Home Courses,Live Online Courses ATTACH;FMTTYPE=image/png:https://prstats.org/wp-content/uploads/2025/10/SPMP01.png GEO:55.378051;-3.435973 END:VEVENT END:VCALENDAR