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Allosteric drugs are increasingly used because they produce fewer side effects. Allosteric signal propagation does not stop at the 'end' of a protein, but may be dynamically transmitted across the cell. Here, we propose that the concept of…

Molecular Networks · Quantitative Biology 2011-11-22 Ruth Nussinov , Chung-Jung Tsai , Peter Csermely

Opioid Use Disorder (OUD) has emerged as a significant global public health issue, with complex multifaceted conditions. Due to the lack of effective treatment options for various conditions, there is a pressing need for the discovery of…

Machine Learning · Computer Science 2023-06-14 Hongsong Feng , Rui Wang , Chang-Guo Zhan , Guo-Wei Wei

Cancer has relational information residing at varying scales, modalities, and resolutions of the acquired data, such as radiology, pathology, genomics, proteomics, and clinical records. Integrating diverse data types can improve the…

Machine Learning · Computer Science 2024-07-29 Asim Waqas , Aakash Tripathi , Ravi P. Ramachandran , Paul Stewart , Ghulam Rasool

This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: (1) identification of novel regulatory variants located in noncoding domains and their function as applied to…

As the past decade barely dawned, a fundamentally novel view of cancer relating to signal transduction through intracellular hormones/growth factors and their subunits began to unfold. Further along, it gained additional substance with the…

Subcellular Processes · Quantitative Biology 2007-12-19 Razvan Tudor Radulescu

Despite all the advances achieved in the field of tumor-biology research, in most cases conventional therapies including chemotherapy are still the leading choices. The main disadvantage of these treatments, in addition to the low…

Tissues and Organs · Quantitative Biology 2024-01-25 Paola Sanchez-Moreno , Juan Luis Ortega-Vinuesa , Jose Manuel Peula-Garcia , Juan Antonio Marchal , Houria Boulaiz

Microfluidic droplet screens serve as an innovative platform for high-throughput biotechnology, enabling significant advancements in discovery, product optimization, and analysis. This review sheds light on the emerging trend of interaction…

Quantitative Methods · Quantitative Biology 2023-09-11 Carolus Vitalis , Tobias Wenzel

Geometric deep learning has demonstrated a great potential in non-Euclidean data analysis. The incorporation of geometric insights into learning architecture is vital to its success. Here we propose a curvature-enhanced graph convolutional…

Quantitative Methods · Quantitative Biology 2023-06-27 Cong Shen , Pingjian Ding , Junjie Wee , Jialin Bi , Jiawei Luo , Kelin Xia

Multifunctional nanomaterials combining diagnosis and therapeutic properties have attracted a considerable attention in cancer research. Yet some important challenges are still to be faced, including an optimal coupling between these two…

Biological Physics · Physics 2019-10-31 Yupeng Shi , Flavien Guenneau , Xiaolin Wang , Christophe Hélary , Thibaud Coradin

Background: A subset of histo-blood group antigens including ABO and Lewis are oligosaccharide structures which may be conjugated to lipids or proteins. They are known to be important recognition motifs not only in the context of blood…

Tissues and Organs · Quantitative Biology 2019-03-08 Viktoria Dotz , Manfred Wuhrer

MOTIVATION: The use of oligonucleotide microarray technology requires a very detailed attention to the design of specific probes spotted on the solid phase. These problems are far from being commonplace since they refer to complex…

Quantitative Methods · Quantitative Biology 2008-02-28 Sébastien Rimour , David Hill , Cécile Militon , Pierre Peyret

Optofluidics is dedicated to achieving integrated control of particle and fluid motion, particularly on the micrometer scale, by utilizing light to direct fluid flow and particle motion. The field has seen significant growth recently,…

Drug resistance is still a major challenge in cancer therapy. Drug combination is expected to overcome drug resistance. However, the number of possible drug combinations is enormous, and thus it is infeasible to experimentally screen all…

Genomics · Quantitative Biology 2018-11-20 Tianyu Zhang , Liwei Zhang , Philip R. O. Payne , Fuhai Li

In this paper, we review recent developments and the role of Graph Neural Networks (GNNs) in computational drug discovery, including molecule generation, molecular property prediction, and drug-drug interaction prediction. By summarizing…

Machine Learning · Computer Science 2025-06-03 Zhengyu Fang , Xiaoge Zhang , Anyin Zhao , Xiao Li , Huiyuan Chen , Jing Li

Modeling the dynamics of cellular differentiation is fundamental to advancing the understanding and treatment of diseases associated with this process, such as cancer. With the rapid growth of single-cell datasets, this has also become a…

Cancer is a complex genetic disease involving uncontrolled cell growth and proliferation, and necessitates effective targeting of dysregulated cellular pathways underlying cancer progression. Multiple genetic and epigenetic alterations…

Other Quantitative Biology · Quantitative Biology 2026-01-28 Manish Kumar

A simple DNA-based data storage scheme is demonstrated in which information is written using "addressing" oligonucleotides. In contrast to other methods that allow arbitrary code to be stored, the resulting DNA is suitable for downstream…

Emerging Technologies · Computer Science 2017-11-15 Gary M. Skinner , Koen Visscher , Masud Mansuripur

Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over…

Molecular Networks · Quantitative Biology 2020-07-10 Victor-Bogdan Popescu , Krishna Kanhaiya , Iulian Năstac , Eugen Czeizler , Ion Petre

Genomic alterations lead to cancer complexity and form a major hurdle for a comprehensive understanding of the molecular mechanisms underlying oncogenesis. In this review, we describe the recent advances in studying cancer-associated genes…

Molecular Networks · Quantitative Biology 2007-12-24 Edwin Wang , Anne Lenferink , Maureen O'Connor-McCourt

Foundation models for single-cell RNA sequencing (scRNA-seq) have shown promising capabilities in capturing gene expression patterns. However, current approaches face critical limitations: they ignore biological prior knowledge encoded in…

Machine Learning · Computer Science 2025-03-04 Mufan Qiu , Xinyu Hu , Fengwei Zhan , Sukwon Yun , Jie Peng , Ruichen Zhang , Bhavya Kailkhura , Jiekun Yang , Tianlong Chen
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