Mustafa Poonawala’s Post

I’m excited to share that I am a co-author of a recently published paper in the AIP Conference Proceedings journal! 🎉 Our research introduces a numerical solution using the Kernelized Rank Order Distance (KROD) method to convert non-spherical data into spherical data. This approach aims to improve the performance of clustering algorithms on complex datasets. You can check out the abstract here: https://lnkd.in/ggqU4djq. I am grateful to my fellow researchers and everyone who supported this work. Looking forward to contributing more to this field! #Research #Publication #DataScience #MachineLearning #Clustering #SparseData

Do you know how to detect changes in videos or trajectories? The techniques to do so are key to unravel biological function and understanding crucial cellular processes🔬. With the blooming of machine learning techniques, there is an opportunity to push the boundaries of what is possible in the characterization of single-particle motion. For this, I invite you to leverage the power of computational techniques to detect and quantify changes in single-particle motion in heterogeneous environments and win the 🌟 2nd Anomalous Diffusion (AnDi) Challenge! The challenge is a fantastic opportunity for you to tackle real-world complexity and contribute to a greater understanding of the microscopic world. 🌐 Whether you're a diffusion practitioner, machine learning developer, microscopy expert, seasoned researcher, or curious newcomer, your perspective is valuable. 🥳 We are already more than 50 participants and the leaderboard is heating up! ⚔️ Together, we will build an objective comparison of methods to analyze single-particle motion. Imagine the impact you could have by contributing your expertise to this groundbreaking challenge. Dive into the details, datasets, and resources on the challenge website: https://lnkd.in/d86jT586 I am participating in the 2nd AnDi Challenge, and you? The challenge is designed to be accessible to anyone with an interest in time series analysis, machine learning, microscopy, or related fields. So, go now to the competition webpage, register, and form your team: https://lnkd.in/dy9FJc4D Let's make a lasting impact on the scientific community! 🌟 #AnDiChallenge #AnomalousDiffusion #AI4Science #ScienceChallenge #Microscopy #SingleParticleTracking #Tracking #DataScience #MachineLearning #HeterogeneousEnvironments #ComputationalTechniques #ScientificCommunity

Andreas Büchse is data scientist at BASF. With his formulas and statistical models, he not only contributes to making the products we use every day more sustainable - he can even use them to avoid experiments on animals or humans. He is convinced that the solutions to today’s challenges lie in chemistry and mathematics. In this interview from the #SmartScientist series, expert Andreas provides exciting insights into his work - and explains why gut instinct plays a role despite all the 'hard facts'. #Research #Innovation #SmartScientists #BASF

Today we wrap up (for now?) a discussion started Friday about UFOs and what is, and is not, science. https://lnkd.in/gCZYRc7V Come see Technoscreed, the newsletter of science and tech humor that anyone can understand!

🚀 As part of our Saturday Science, we share the recent super-fast software success for the genomics community! 🚀 Our very own Dr Sarah Beecroft and Michael Roach from the Adelaide Centre for Epigenetics and the SAiGENCI, working with a team from Flinders University, published a paper on a cutting-edge read-coverage analysis tool for massive (meta)genomics datasets, Koverage! 🧬📊 📰 Published in the Journal of Open Source Software (JOSS), Koverage is here to optimise read-coverage calculations by eliminating I/O bottlenecks and enhancing scalability. 🌐💻 🔍 What's cool about Koverage: ✨ Makes working with big DNA datasets much faster ✨ Uses fancy tech called Snakemake for super-smooth operation ✨ Can figure out the makeup of different living things in your samples 🛠️ Koverage is like a superhero for scientists, written in a language called #Python, and you can easily get it on your computer. All you need are two things: a special DNA file and your experiment's results. 🔥 Benchmarks on Pawsey Supercomputing Research Centre’s Setonix HPC show Koverage outperforming other tools, with mapping and kmer methods significantly faster. 🚀 Read the full paper in JOSS to discover Koverage and its impact on genomics research! https://bit.ly/3PlN1Z2 📑 🔬 #SaturdayScience #Genomics #OpenSource #ResearchRevolution #Koverage #JOSSPublication 🧬✨

I am delighted to share that I have completed the 'Cheminformatics: Tools and Applications' course from Neovarsity! Here is the Certificate of completion (https://lnkd.in/ddN_V_n6). This comprehensive program, led by experienced instructors, provided me with in-depth knowledge and practical skills across the entire cheminformatics pipeline for drug discovery. Throughout the course, I learned to: - Accurately represent molecules - Analyze chemical databases - Generate features for QSAR and machine learning algorithms - Explore potential molecules in chemical space The course included engaging capstone projects, allowing me to apply my skills to real-world scenarios and build a strong portfolio. These projects have equipped me with the expertise needed for drug discovery, materials science, and agricultural research. I'm thrilled to have this new skill set and look forward to leveraging it in future projects. A big thank you to Neovarsity for this excellent learning experience! #Cheminformatics #MachineLearning #DrugDiscovery #ArtificialIntelligence #ContinuousLearning #ProfessionalDevelopment

Great new preprint from the TIER2 Project, giving insights into the applicability of concepts of reproducibility and Open Science regarding qualitative research! https://lnkd.in/dd3bURMs

🚨 New preprint! 🚨 I'm delighted to share that we preprinted our comprehensive review of the intersections between #reproducibility, #openscience and #qualitativeresearch in late December. Are you interested to know how the qualitative research community frames its relationship to reproducibility (hint: it's complicated!) and how we understand barriers to and enablers of #openqualitativeresearch? Then give our paper a read and let us know what you think about our study and our results. Many thanks to my dedicated study team and co-authors, Sven Ulpts, Agata Bochynska, Eva Kormann, Matthew Good, Barbara Leitner and Tony Ross-Hellauer within the TIER2 Project. Link in the comments.