Call for Papers

Bio-Inspired Computing and Machine Learning Analytics for a Future-Oriented Mental Well-Being

Special issue in SLAS Technology – completed manuscripts accepted until July 30, 2024.

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Guest Editors:

Chinmay Chakraborty, Ph.D.
Birla Institute of Technology, Jharkhand, India

Bhuvan Unhelkar, Ph.D.
University of South Florida, USA

Saïd Mahmoudi, Ph.D.
University de Mons, Belgium

The Special Issue proposes bio-inspired computing and machine learning analytics for mental well-being in the field of life sciences innovation. It justifies the need for this special issue by highlighting the emerging behavioral health technologies that integrate big biological data, artificial intelligence, cloud/fog computing, machine learning, bio-inspired computation, the Internet of Medical Things, wireless technologies, security and privacy, semantic databases and content. The large volume of behavioral health data, often referred to as big data, requires scalable machine learning, deep learning and intelligent algorithms to process it effectively. By intelligently investigating and collecting vast amounts of biological data, sensors can improve the decision-making process and facilitate early disease diagnosis. The ultimate goal is to revolutionize the delivery of biological services through a medical assistive environment and facilitate the independent living of patients.

Keywords include:

  • Wireless body area sensor networks for bio-inspired Health 4.0
  • Bio-inspired Health 4.0 Cyber-Physical System (HCPS)
  • Decision-Making Unit (DMU) for Health 4.0
  • Recent trends in sensor technology, and wearable computing
  • Healthcare sensor data analytics
  • Wireless and wearable sensors for bio-inspired health informatics
  • Cloud computing and big data technologies for sensor data processing
  • Complex sensors data handling
  • Internet of things health for next generation networks
  • Remote human’s health and activities monitoring
  • Smart sensors technologies for healthcare
  • Big medical data analytics
  • Optimal sensors establishment algorithms
  • Mobility enhancement of sensors data streams
  • Advances of data acquisition to data fusion
  • Decision-making systems for sensors data
  • Artificial intelligence for health informatics
  • Data mining and fusion algorithms for WBAN
  • Health sensor data management
  • Sensor informatics for physical activity monitoring
  • Sensors for VR/AR, mixed reality, data visualization

Submit your manuscript before July 30, 2024. All submitted papers will be subject to peer-review to ensure scientific rigor, clarity of expression and integration with other contributions in the SLAS Technology Special Issue.

Publication note: After submissions are accepted, they typically publish online ahead-of-print within 30 days and become immediately searchable and citable with a DOI.

Questions? Please e-mail: cchakrabarty@bitmesra.ac.in

High-Throughput Mass Spectrometry in Drug Discovery

Special issue in SLAS Technology – completed manuscripts accepted until June 30, 2024.

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Guest Editors:

Chang Liu, Ph.D.
SCIEX

The rapid development of high-throughput mass spectrometry technologies has enabled MS to be an invaluable analytical tool in various disciplines, industries and research fields. It has become particularly central to new drug discovery and development, broadly deploying mass spectrometry at every phase. The pharmaceutical industry has become one of the main drivers of technological development in mass spectrometry.

In the proposed special issue, we would like to present current technical developments in the fields, including AEMS, IR-MALDESI, LAP-MALDI, DESI, nano-DESI, MALDI, etc. and their applications in high-throughput drug discovery workflows.

Keywords include:

  • Mass spectrometry
  • High-throughput analysis
  • Drug discovery
  • Automation
  • Hit identification
  • Data processing

Submit your manuscript before June 30, 2024. All submitted papers will be subject to peer-review to ensure scientific rigor, clarity of expression and integration with other contributions in the SLAS Technology Special Issue.

Publication note: After submissions are accepted, they typically publish online ahead-of-print within 30 days and become immediately searchable and citable with a DOI.

AI-Driven Predictive Modeling for Disease Prevention and Early Detection

Special issue in SLAS Technology – completed manuscripts accepted until July 30, 2024.*

*All published special issue submissions will receive 30% off the APC fee!

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Guest Editors:

Bikash Behera, Ph.D.
Indian Institute of Science Education and Research

Azeem Irshad, Ph.D.
Department of Computer Science and Software Engineering, International Islamic University

Imad Rida, Ph.D.
University of Technology of Compiègne

Mohammad Shabaz, Ph.D.
Model Institute of Engineering and Technology

Traditional methods of diagnosis and prediction often rely on observable symptoms and historical data, which may not be sufficiently accurate or timely. With artificial intelligence (AI), healthcare providers can analyze an array of variables, from genetic markers to lifestyle choices and even environmental factors, to predict the likelihood of disease occurrence and progression. Predictive modeling using AI is increasingly becoming an indispensable tool for disease prevention and early detection. By leveraging machine learning algorithms and predictive analytics techniques, this approach can identify patterns and trends that might not be apparent through traditional statistical methods. By leveraging AI's predictive capabilities, the healthcare sector can shift from a predominantly reactive model to a more proactive and preventative one. Furthermore, AI-driven predictive modeling opens the door to personalized medicine on an unprecedented scale.

Using machine learning algorithms that analyze genetic, epigenetic and proteomic data, personalized treatment plans can be devised for individual patients. However, implementing AI-driven predictive modeling is experienced with complex challenges such as data sensitivity, incomplete and inconsistent data and missing values. Addressing these difficulties is crucial for the successful implementation and create a healthcare system that truly harnesses the power of AI for the benefit of all.

This special issue will serve as a platform for researchers, clinicians, policymakers and scholars to share their cutting-edge research, findings, methodologies, case studies and advancements that explore the transformative impact of AI in the realm of disease prevention and early detection.

Submit your manuscript before July 30, 2024. All submitted papers will be subject to peer-review to ensure scientific rigor, clarity of expression and integration with other contributions in the SLAS Technology Special Issue.

Publication note: After submissions are accepted, they typically publish online ahead-of-print within 30 days and become immediately searchable and citable with a DOI.

Questions? Please e-mail Bikash Behera, dr.bikash.behera@ieee.org

3D Printing Microfluidics Devices

Special issue in SLAS Technology – completed manuscripts accepted until October 1, 2024.

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Guest Editors:

Roman Voronov, M.S., Ph.D.
New Jersey Institute of Technology

Sergei Chapek, Ph.D.
Ergometa, Inc.

SLAS Technology Guest Editors Roman Voronov, M.S., Ph.D. (New Jersey Institute of Technology) and Sergei Chapek, Ph.D. (Ergometa, Inc.), invite the submission of manuscripts about novel advances and applications in “3D Printing Microfluidics” for publication in a 2023-2024 Special Issue. SLAS Technology has a 2.8 Impact Factor / 3.1 5-Year Impact Factor / 5.4 CiteScore and authors participating in the Special Issue will receive a 30% discount on the Open Access fee.

The Special Issue arrives at a time when 3D printing has evolved beyond a mere prototyping method to become a futuristic approach to the fabrication of microfluidic devices. In this special issue, we delve into the captivating world of 3D-printed microfluidics. Over the years, 3D printing technology has facilitated revolutionary breakthroughs in microfluidics. This emerging discipline marries the precision of 3D printing with the complexity of microfluidic devices, empowering scientists, and engineers to craft highly customizable and efficient tools for a range of research and applications. In this edition, we explore the exciting developments, novel designs and forefront applications at the juncture of 3D printing and microfluidics. Join us as we unveil the extraordinary potential harbored in this transformative field and learn how it is sculpting the future of 3D-printed microfluidic devices.

Voronov and Chapek seek high-quality, short or full-length research reports, reviews and perspectives related to novel advances and applications in 3D Printing Microfluidics. Manuscripts are welcome from academia, industry and vendors. Areas of particular interest include, but are not limited to:

  • Printer Instrumentation & Innovative Technologies for 3D Printing Microfluidics Devices
  • Methods & Strategies for 3D Printing Microfluidics Devices
  • Resins & Materials for 3D Printing Microfluidics Devices
  • Biological Applications of 3D Printed Microfluidics Devices
  • Non-Biological Applications of 3D Printed Microfluidics Devices
  • Analysis of 3D Printed Microfluidics Devices
  • Mathematical Modeling of Microfluidics Device 3D Printing Process
  • 3D Printed Lab-on-a-Chip, Organ-on-a-Chip, Human-on-a-Chip

Submit your manuscript before October 1, 2024. All submitted papers will be subject to peer-review to ensure scientific rigor, clarity of expression and integration with other contributions in the SLAS Technology Special Issue.

Publication note: After submissions are accepted, they typically publish online ahead-of-print within 30 days and become immediately searchable and citable with a DOI.

Questions? Please e-mail rvoronov@njit.edu AND sergei@ergometa.com.

Outcomes From the Antiviral Drug Discovery (AViDD) Centers and Others for Pathogens of Pandemic Concern

Special issue in SLAS Discovery – completed manuscripts accepted until July 1, 2024.

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Guest editors:

Timothy Spicer, Ph.D.
The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology

Louis Scampavia, Ph.D.
The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology

Following the COVID-19 pandemic, many centers and labs, including those involved in the National Institute of Allergy and Infectious Diseases Antiviral Drug Discovery (AViDD) program, have been working diligently on initiatives to help prepare for the next viral pandemic. This includes anything from early drug discovery encompassing a broad range of approaches, to hits to leads transition for small molecules and biologics that are critical for success in the clinics against pathogenic viruses.

Many investigators have combined their expertise to push forward novel approaches to validate and pursue early through late-stage viral targets. They incorporate efforts across the institutes worldwide and, notably, include resources from industrial partners. The sum of their efforts will drive small molecules and biologics into therapeutic development pipelines. 

This special issue will focus on all areas of this important discovery initiative, including all facets of drug discovery, some of which include:

  • High-throughput screening
  • DNA-encoded library screening
  • AI and structural modeling
  • Medicinal chemistry
  • Antibody/nanobody engineering

Submit your completed manuscript before July 1, 2024.  

Robotics in Laboratory Automation

Special issue in SLAS Technology – completed manuscripts accepted until May 1, 2024.

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The SLAS Technology Guest Editorial Board invites the submission of manuscripts covering novel advances and applications in robotics for laboratory workflow automation for publication in a Special Issue. 

Members of the Guest Editorial Board include:

  • Kerstin Thurow, Ph.D. (Center for Life Science Automation at the University of Rostock)
  • Oliver Peter, Ph.D. (Idorsia Pharmaceuticals)
  • Patrick Courtney, Ph.D. (Association Consortium Standardization in Lab Automation (SiLA))
  • Károly Széll, Ph.D. (Alba Regia Technical Faculty of the Óbuda University)
  • Ádám Wolf, M.Sc. (Takeda)

SLAS Technology is seeking high-quality reviews, innovative implementation reports and perspectives on supportive robotics solutions in life science laboratory workflow automation. Manuscript proposals (abstracts) are welcome from academia, industry and vendors. Areas of particular interest include, but are not limited to:

  • Novel robotics solutions for supportive laboratory activities. Applications may include:
    • labware transportation,
    • cleaning,
    • disinfection,
    • error detection and handling
    •  and collaborative applications
  • Corresponding aspects of the automation framework such as:
    • integration approaches,
    • physical and logical interoperability,
    • knowledge representation,
    • ontologies,
    • process control,
    • simulation
    • and optimization
  • Historical perspectives

Submit your completed manuscript before May 1, 2024.

Protocols in 3D Biology: Technologies and Methodologies Reshaping 3D Cell Culture

Special issue in SLAS Discovery – completed manuscripts accepted until May 31, 2024.

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Guest Editors:

Glauco Souza, Ph.D.
Greiner Bio-One 

Madhu Nag, M.B.S., Ph.D.
InSphero

Evan Cromwell, Ph.D.
Protein Fluidics

This special issue will focus on protocols related to technologies and methodologies that are reshaping the field of 3D biology. It aims to publish detailed protocols in 3D cell culture, including protocols applying novel tools, organ-on-a-chip, and/or the integration of AI to augment throughput, automation, analysis, and control in 3D biology.

The Importance of Protocols

Protocols provide step-by-step instructions, methods and other criteria that enable investigators to conduct and expand research. Protocols published in SLAS journals benefit from:

  • High distribution and reach – SLAS journals received a combined full text usage of over 1.2 million reads in 2021 and growing.
  • Low submission barrier – Protocols can be developed from on-hand documentation of methods and solutions.
  • Validated results – All articles are peer reviewed, adding a level of rigor and validation to the final publication.
  • Open access publication – Authors retain the reproduction rights of the final article.

Keywords

  • 3D cell culture
  • Protocols
  • Drug discovery
  • Organ-on-a-chip
  • Microfluidics
  • Artificial Intelligence
  • Automation
  • High-throughput
  • Liquid Handling

Submit your manuscript before May 31, 2024. All submitted papers will be subject to peer-review to ensure scientific rigor, clarity of expression and integration with other contributions in the SLAS Discovery Special Issue.

Questions? Please e-mail SLAS Publishing Manager Jenny Cunningham (jcunningham@slas.org).