?? Webinar incoming! Dive into the latest computational tools driving breakthroughs in Spatial Genomics analysis with Dr. Matthew Bernstein Dr. Bernstein will share insights from his latest projects in spatial transcriptomics, showcasing cutting-edge analytical approaches that are shaping the future of genomics research. ?? Date:?March 26th ? Time:?12-1pm EST ?? Location: Virtual (link provided upon registration) Secure your spot today and take a deep dive into the next generation of Spatial Genomics analysis. https://lnkd.in/eU78pmDN
Watershed Bio
生物技术研究
Cambridge，Massachusetts 2,989 位关注者
Powering insights across the life sciences Learn more at watershed.bio
关于我们
Watershed is the complete solution for biological data analysis, discovery, and collaboration. Our platform gives every lab the power of a dedicated computational core in one integrated environment, purpose-built for biology: - Securely access, manage, and harmonize complex datasets, including public and controlled-access data. - Run and track analyses on every data type using customizable workflows, including ready-to-use AI tools, all while upholding FAIR principles. - Leverage powerful supercomputing infrastructure and resources to complete large-scale analyses in minutes instead of weeks. - Access a dedicated bioinformatics team for everything from technical support to rigorous partnership. Email [email protected] or visit our website at https://watershed.bio to learn more or schedule a live demo.
- 网站
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https://watershed.bio
Watershed Bio的外部链接
- 所属行业
- 生物技术研究
- 规模
- 11-50 人
- 总部
- Cambridge，Massachusetts
- 类型
- 私人持股
- 领域
- bioinformatics、biological data analysis、drug discovery、genomics、transcriptomics、proteomics、epigenomics、sequencing data analysis、drug development、biopharma、biological research和biomedical research
地点
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主要
获取路线
US，Massachusetts ，Cambridge
Watershed Bio员工
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Ethan Van der Heide
Lead Recruiter at Watershed Bio
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Mark Kalinich, MD, PhD
Co-founder | Physician-Scientist
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Andrew Wight
Bioinformatician, immunology & flow cytometry nerd, and platform builder with experience in every stage of the laboratory journey.
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Katherine Plumlee
Chief Strategy Officer at Reflexivity
动态
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?? Thanks to everyone who stopped by our booth at Society of Toxicology (SOT) last week! We had a great time connecting with toxicology experts and our partners at Rancho BioSciences. #Toxicology #SOT2025 #Biotech #LifeSciences #Collaboration
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?? We're obsessed with "Way Cool Genomics!" a video series launched by Eric Green, M.D., Ph.D., Director of the National Human Genome Research Institute (NHGRI), showcasing impactful and innovative applications of genomics. ?? The first episode, titled "Way Cool Genomics: eDNA in the air!", explores the significance of environmental DNA (eDNA) in monitoring biodiversity. Check it out! https://lnkd.in/eQeFzNE4
Way Cool Genomics: eDNA in the air! #waycoolgenomics #edna #biodiversity #dna
https://www.youtube.com/
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?? Get to know Matthew Bernstein, the host of next week's Watershed webinar! Register today to save your spot: ?https://lnkd.in/ewnh8Tgt
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Society of Toxicology (SOT) is in full swing! Explore how to access #hpc resources and bring your team together on analyses at booth 763. ?? Congratulations to Dorothy You on winning an Apple Watch yesterday from our gacha machine! ? #SOT #HPC #Watershedbio
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Maximize your Society of Toxicology (SOT) experience with us! We have a full schedule of speaking sessions and poster presentations highlighting our team's expertise in turning data into insights. Discover cutting-edge solutions data solutions & see how we're transforming toxicology with innovative data solutions at booth #761 and presentations. Speaking Session: Utilizing LLMs to gain insights from biological knowledge graphs. Wed, March 19th, 3:05 PM, Icon Room W203A. #LLM #Toxicology Poster Presentations: Harnessing Human Omics Data and ML, Combined with Human Insights, to Revolutionize Gene Target Safety Evaluation Mon, March 17th, 1:45 PM, W Hall A2, Poster #3565/N719. #Omics #MachineLearning Automated Extraction of Biotransformation Data from Metabolic Schemas Using Geometric Criteria and Large Language Models Mon, March 17th, 1:45 PM, W Hall A2, Poster #4067/K566. #Metabolism #AI A Comprehensive Dataset of Pharmacokinetic Parameters for Recommended Doses of Drugs: Enabling Drug Repositioning and Pharmacological Analysis Tue, March 18th, 9:15 AM, W Hall A2, Poster #4068/K567. #Pharmacokinetics #DrugDiscovery Schedule a consultation: https://hubs.ly/Q03bZGDx0 Don't miss out! #SOT2024 #Toxicology #LLM #DataScience #Biomarkers #Genomics #Pharmacokinetics"
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?????? Join us at Booth 763!
?? We’re looking forward to a brief escape from the snowy weather as we travel to Florida in a few weeks for Society of Toxicology (SOT). Join us as we soak up the sun and chat all things bioinformatics, computational biology and beyond! Make sure to book your demo in advance: https://watershed.bio/demo #SOTAnnualMeeting #2025SOT
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? Don't forget to register for our upcoming #webinar! Dr. Matthew Bernstein will share insights from his latest projects in #spatialtranscriptomics, showcasing cutting-edge analytical approaches that are shaping the future of #genomics research.??? https://lnkd.in/ewnh8Tgt ?? Date:?March 26th ? Time:?12-1pm EST ?? Location: Virtual (link provided upon registration)
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Working in genomics and wanting to learn how to utilize the command line in your analysis??Check out this post to learn about some simple AWK?commands that could save you time. ?
Director of Bioinformatics | Cure Diseases with Data | Author of From Cell Line to Command Line | Educator YouTube @chatomics
If you work in bioinformatics, AWK is a must-learn. ?? Here’s how to split large files by chromosome, sample, or any column using simple one-liners. ???? 1/ Splitting a BED file by chromosome Sort the file, remove "chr" prefix, and split into separate files: cat nexterarapidcapture_exome_targetedregions_v1.2.bed | \ sort -k1,1 -k2,2n | sed 's/^chr//' | awk '{close(f);f=$1}{print > f".bed"}' 2/ Another way to split by chromosome (simpler) awk '{print $0 >> $1".bed"}' example.bed This creates 1.bed, 2.bed, etc. 3/ Split a file by any column (e.g., sample ID, gene name, etc.) Change $1 to any column number (e.g., $4 for sample name). awk '{print >> $1; close($1)}' input_file 4/ Example: BED file splitting by chromosome Input (example.bed): chr1 12 14 sample1 chr1 10 15 sample2 chr2 10 20 sample1 chr2 22 33 sample2 Command: awk '{print >> $1".bed"; close($1".bed")}' example.bed Output: ? chr1.bed ? chr2.bed 5/ Split by sample name instead of chromosome awk '{print >> $4".bed"; close($4".bed")}' example.bed This creates sample1.bed, sample2.bed, each containing relevant lines. 6/ Why is this useful? ? Quickly break large files into smaller chunks ? Useful for parallel processing ? Works with BED, VCF and more 7/ Key takeaways: ? AWK is a powerful tool for handling structured text ? You can split files by any column Combine it with sort, sed, and other UNIX tools for even more power 8/ Action item: Try running these AWK one-liners on your own datasets. You'll be surprised how much time they save! ? What’s your favorite AWK trick? Share below! ?? I hope you've found this post helpful. Follow me for more. Subscribe to my FREE newsletter https://lnkd.in/erw83Svn
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???? We are thrilled to announce that we are furthering our mission of empowering #biopharma teams with game-changing computational tools by partnering with Rancho BioSciences. By combining Watershed’s revolutionary #bioinformatics operating system with Rancho’s domain expertise and excellent solution development support, we aim to drive the next generation of biomedical breakthroughs. Come innovate with us! #HPC #biotech #innovation
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