Hello everyone! My name is Hafsa, and I am a master’s student studying Biotech/Bioinformatics, and I have a BS in biochemistry. I’m interested in space biology and in learning more about proteomics and the analysis of OSDR datasets. I’m looking forward to learning from the group and contributing where I can!
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Good timing on Proteomics, the OSDR/Genelab proteomic pipeline is just in the final stages of development to be released!
Ie, will be more standardized data for re-use 
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Hi everyone, my name is Katelyn. I’m an undergraduate(freshmen) biochemistry major. My main interests are general space biology/Space biology Transcriptomics, and learning more about open science and data analysis in general. I am excited to meet you all, as well as learn and contribute from you!
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Hi everyone! My name is Tamara, and I am an undergrad student studying Bioinformatics. I have a background in R, Python, and Linux for computational biology workflows. I’m very interested in space biology, multi-omics data integration, and analyzing OSDR datasets. I look forward to learning from all of you and contributing where I can!
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Hi everyone,
My name is Cheng-Hsun Tsai, but please feel free to call me Teddy.
I graduated with a bachelor’s degree in Biomedical Science and Engineering this past June, and my expertise lies in machine learning and bioinformatics. I recently submitted my first first-author paper to Artificial Intelligence in Medicine, which proposes a novel two-stage calibration framework for AFT survival analysis under highly censored data conditions.
Starting in August, I joined a tumor evolution lab as a Research Assistant to pursue my research passions. My long-term goal is to investigate when and where cellular carcinogenesis is triggered by the space environment (such as microgravity and cosmic radiation) from the perspectives of clonal evolution and phylogenetics.
I joined this working group to exchange ideas and learn from experts in the field. I am thrilled to be here, look forward to collaborating with you all, and would love to connect and chat!
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Hi everyone,
My name is Agustina (or Agus for short). I graduated as a biologist last year (B.Sc. Biological Sciences, Biotechnology orientation, Universidad Favaloro, Argentina). My undergraduate research at IMETTyB studied stem cell therapy in an ovine model of acute myocardial infarction, combining wet-lab work with a transcriptomic component (differential expression from public GEO data, then over-representation analysis triangulated across Metascape, Enrichr and ToppGene).
What I enjoy most is the interpretation end: taking a list of differentially expressed genes and working out what it actually means biologically. I recently completed the NASA GL4U course, and I am working on my Python and R.
I joined because space biology fascinates me and I want to contribute to real projects while building my bioinformatics skills. I’d be glad to help on sub-projects where enrichment and interpretation of DE results would be useful, across organisms and data types; if anyone has something at that stage, I’d love to hear about it.
Looking forward to meeting you all! 
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Hi, I am Dr. Nitin Bayal. I am a postdoc at the Dept. of Computing, University of Turku, Finland. I am working in the research areas of the gut-brain axis and analyzing multi-omics data from the Finnish population cohorts.
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Hi, Dr. Nitin Baya. I am Michelle. Very interesting work! Which OSD datasets have you been exploring for this research?
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I just started exploring OSDR platform and hopefully engage with others in upcoming monthly meetings.
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For your research, I suggest exploring OSD-914 and OSD-905. I think you may find some interesting connections with your work.
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Thanks Michelle for the links, I will check these
Yes, of course! Here are the links:
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Hi Agustina! We have a subgroup that aligns well with your research interests. You could contact @kykamal for more information. His email is kykamal@iastate.edu.
Hi Michelle! Thank you, I’ll get in touch.
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The open-source repository configuration has been expanded to integrate a programmatic optimization module utilizing SciPy’s Levenberg-Marquardt regression scripts. This optimization layer is engineered to directly ingest raw, heterogeneous metadata configurations from datasets like GLDS-739. The pipeline maps the high-throughput sequencing payload metrics (Read_Depth) to target log-scale capacity vectors while executing runtime error suppression using variance inputs derived from sample-specific rRNA_Contamination_Pct arrays. This prevents technical laboratory batch noise from disrupting gradient optimization loops. The global solver optimizes parameters dynamically against non-linear timelines, allowing teams to isolate exact numerical value outputs for cytoskeletal mechanosensitive gain ([\beta ]) and tissue relaxation constraints ([\tau ]) asynchronously across complex spaceflight datasets.
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Hello everyone. I am PhD Cell Biology with concentration in Bioinformatics. During my research I have developed a unique equation to analyze proteomics data. Mice raised at three different temperatures, 30 °C, 23 °C, and 6 °C, were subjected to proteomic analysis. There Brown Adipose Tissues were isolated and cytoplasmic mitochondria and lipid droplet-anchored mitochondria proteome was performed. The equation developed tend to find Relative Strength of Expression (RSE) of proteins at varying conditions (temperatures). It helped in determining a previously unidentified network termed as HEAT Cycle (https://www.sciencedirect.com/science/article/pii/S1388198121001207). I am interested in joining Proteomic Group to analyze proteome data gathered at different conditions.
Thanks.
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