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Biotech IT Solutions
Gaithersburg, United States
B
1-10 Employees
2020
Key takeaway
The company leverages in-house data to create models and offers IT solutions designed to enhance growth in the biotechnology sector, highlighting the synergy between Biotech and IT.
Reference
Core business
Biotech-IT Solutions
Experience accelerated growth and unlock potentials
DataHow
Zurich, Switzerland
A
1-10 Employees
2017
Key takeaway
DataHow is a Swiss technology company that specializes in data analytics and bioprocess modeling, emphasizing the transformative potential of data and digital technologies in biopharma operations. Their innovative platform, DataHowLab, offers in-silico simulations and guided workflows that enhance development efficiencies and address specific challenges in bioprocess development.
Reference
Core business
Digital Bioprocess Solutions - Datahow Technology
DataHow is specialized in data analytics and bioprocess modeling
Clovertex Group LLC
Boston, United States
B
51-100 Employees
2018
Key takeaway
Clovertex specializes in managing large-scale big data platforms and offers expertise in high-performance computing (HPC) tailored for scientific research, including applications relevant to biotechnology. Their unique methodologies and experience in cloud migration and data processing provide optimized solutions for the biopharma sector, enabling faster data analysis and reporting.
Reference
Core business
Home
Data Expertise for Biotech and Pharma. Process, analyze, and report faster than ever on AWS. Learn more.
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Insilicogen
Yongin-si, South Korea
A
11-50 Employees
2005
Key takeaway
Insilicogen has been building bio big data for 20 years, positioning itself as a leader in the field. The company focuses on providing efficient processes through its expertise in data production, archiving, modeling, and analysis.
Reference
Core business
Insilicogen, Inc.
바이오 빅데이터의 리더 (Read Data, Lead Big)
Quantori
Cambridge, United States
B
251-500 Employees
-
Key takeaway
The company specializes in genomic analysis software and data management infrastructure, which are crucial for advancing big data applications in biotechnology. Their focus on high-performance computing platforms and AI-driven solutions enhances treatment effectiveness and supports scientific research in life sciences and healthcare.
Reference
Service
AWS Data Science | Quantori
Lifebit
London, United Kingdom
A
51-100 Employees
2017
Key takeaway
Lifebit is a precision medicine software company that specializes in creating data platforms for sensitive genomic and biomedical datasets. Their advanced systems facilitate secure access and analysis of large volumes of biomedical data, particularly in cancer and rare disease research, thereby addressing key challenges in precision medicine and genomics.
Reference
Core business
Pioneering Federated Trusted Research Environments - Lifebit
Building a global network for scientific collaboration and discovery with the world’s first federated trusted research environment for genomic data.
BioMap
-
- Employees
2020
Key takeaway
BioMap is transforming biotechnology by utilizing Foundation Models to enhance various applications, including therapeutic antibodies and designed proteins, even with limited data. Their innovative approach integrates advanced AI and supercomputing to develop models that predict biological behavior, ultimately aiming to leverage data for drug development and improving lives.
Reference
Core business
Homepage — BioMap
BioTeam
Middleton, United States
B
11-50 Employees
2001
Key takeaway
BioTeam specializes in creating integrated data ecosystems that serve as the essential IT backbone for modern biomedicine, addressing complex challenges in research and operations. Their expertise in data science and technology empowers scientists to enhance the speed and impact of biomedical discoveries.
Reference
Core business
BioTeam - Life Sciences IT Consulting
A scientific IT consulting company at the intersection of science, data and technology, BioTeam is relentlessly focused on closing the gap between what scientists want to do with data—and what they can do.
DSBio-consulting
Manchester, United Kingdom
A
1-10 Employees
2019
Key takeaway
DSBio-consulting specializes in bioinformatics and data science, offering extensive data analysis services for genomics and systems biology research. Their expertise includes high-throughput sequencing data analysis and precision medicine, making them well-equipped to handle big data challenges in biotechnology.
Reference
Core business
Home - DSBio-consulting
Analysis of BIG data for trends, insights and discoveries in biology and business domainsBioinformatics and Business Analytics Speed up your research and unleash the power of your data with quality data analysis Contact Us SERVICES Read more Bioinformatics Data Analysis Our services are available at affordable prices for a wide variety of data analysis (bioinformatics …
ATGENOMIX
Taipei, Taiwan
1-10 Employees
2015
Key takeaway
Atgenomix is a cloud-native biomedical informatics platform that specializes in unlocking complex genomic insights through advanced data integration and analytics. Their focus on operationalizing biomedical data and machine learning aligns with the growing importance of big data in biotechnology, particularly in the context of precision medicine and Next Generation Sequencing (NGS) testing.
Reference
Core business
Atgenomix | Data and machine learning | BioMedical IT
Atgenomix provides an open standard and unified platform for operationalizing biomedical data, analytics, and machine learning.
Technologies which have been searched by others and may be interesting for you:
Big Data Biotechnology involves the use of large datasets to enhance research and development in the field of biology and health sciences. This approach leverages advanced data analytics, machine learning, and computational tools to analyze complex biological information. By integrating diverse data sources such as genomic sequences, clinical data, and environmental factors, researchers can uncover patterns and insights that drive innovation in drug discovery, personalized medicine, and agricultural biotechnology. The application of big data techniques enables biotechnologists to make more informed decisions, improve the efficiency of experiments, and accelerate the development of new therapies. As a result, the intersection of big data and biotechnology is transforming the way biological research is conducted and fostering a deeper understanding of biological processes.
The integration of Big Data in biotechnology is significantly transforming healthcare research by enabling the analysis of vast amounts of biological and clinical data. This innovation allows researchers to identify patterns and correlations that were previously undetectable. For instance, by leveraging genomic data alongside electronic health records, scientists can better understand disease mechanisms and patient responses to treatments. Moreover, the use of advanced analytics and machine learning algorithms empowers researchers to personalize medicine. By analyzing large datasets, they can predict the efficacy of specific therapies for individual patients, leading to more effective treatment plans. As a result, Big Data biotechnology not only accelerates the pace of research but also enhances the precision and reliability of healthcare solutions.
1. Data Analytics Platforms
These platforms are essential for processing and analyzing vast datasets in biotechnology. They utilize algorithms and statistical methods to extract meaningful insights from complex biological data.
2. Machine Learning Frameworks
Machine learning frameworks are used to develop predictive models that can identify patterns in biological data. These tools enhance the ability to make data-driven decisions in research and development.
3. Cloud Computing Services
Cloud computing provides the necessary infrastructure for storing and processing large volumes of data. It allows biotechnology firms to scale their operations and collaborate effectively across different locations.
4. Bioinformatics Tools
Bioinformatics tools are crucial for managing and analyzing biological data, including genomic sequences and protein structures. They support various applications, such as drug discovery and personalized medicine.
5. Visualization Software
Visualization software helps researchers interpret complex data through graphical representations. It facilitates better understanding and communication of research findings, driving innovation in biotechnology.
Big Data Biotechnology significantly enhances drug discovery processes by leveraging vast amounts of biological and chemical data. Analyzing large datasets allows researchers to identify potential drug targets more efficiently. By utilizing machine learning algorithms, scientists can predict how different compounds interact with biological systems, streamlining the screening process. Moreover, the integration of genomic and proteomic data enables a deeper understanding of disease mechanisms. This comprehensive approach leads to more accurate models for testing drug efficacy and safety, ultimately accelerating the transition from laboratory research to clinical trials. The synergy of big data analytics in biotechnology not only shortens the drug discovery timeline but also increases the likelihood of successful outcomes.
Big Data Biotechnology encounters significant challenges in data security due to the sensitive nature of the information involved. Protecting personal health data and proprietary research findings necessitates robust security measures. Cyber threats, including data breaches and ransomware attacks, pose constant risks, as hackers target valuable biotechnological data. Furthermore, compliance with regulations such as HIPAA and GDPR complicates security efforts, requiring organizations to implement stringent data protection protocols. The integration of vast datasets from various sources increases vulnerability, making it difficult to maintain consistent security standards across all platforms. Addressing these challenges requires a combination of advanced technology, ongoing training for staff, and a proactive approach to risk management.
Some interesting numbers and facts about your company results for Big Data Biotechnology
| Country with most fitting companies | United States |
| Amount of fitting manufacturers | 9311 |
| Amount of suitable service providers | 8136 |
| Average amount of employees | 11-50 |
| Oldest suiting company | 2001 |
| Youngest suiting company | 2020 |
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Some interesting questions that has been asked about the results you have just received for Big Data Biotechnology
What are related technologies to Big Data Biotechnology?
Based on our calculations related technologies to Big Data Biotechnology are Biomedical (Red), Bioinformatics (Gold), Environmental Biotechnology (Grey), Agricultural Biotechnology (Green), Food Related Biotechnology (Yellow)
Which industries are mostly working on Big Data Biotechnology?
The most represented industries which are working in Big Data Biotechnology are IT, Software and Services, Biotechnology, Other, Pharmaceuticals, Healthcare
How does ensun find these Big Data Biotechnology Companies?
ensun uses an advanced search and ranking system capable of sifting through millions of companies and hundreds of millions of products and services to identify suitable matches. This is achieved by leveraging cutting-edge technologies, including Artificial Intelligence.
