Related papers: Characterizing interdisciplinarity in drug researc…
Appropriate evaluation and experimental design are fundamental for empirical sciences, particularly in data-driven fields. Due to the successes in computational modeling of languages, for instance, research outcomes are having an…
Drug combination therapy is a well-established strategy for disease treatment with better effectiveness and less safety degradation. However, identifying novel drug combinations through wet-lab experiments is resource intensive due to the…
As the impact of AI on various scientific fields is increasing, it is crucial to embrace interdisciplinary knowledge to understand the impact of technology on society. The goal is to foster a research environment beyond disciplines that…
Drug repurposing is an effective strategy to identify new uses for existing drugs, providing the quickest possible transition from bench to bedside. Existing methods for drug repurposing that mainly focus on pre-clinical information may…
An innovative approach to analyze the complexity of translating novel molecular entities and nanomaterials into pharmaceutical alternatives (i.e., knowledge translation, KT) is discussed. First, some key concepts on the organization and…
Scientific publications about machine learning in healthcare are often about implementing novel methods and boosting the performance - at least from a computer science perspective. However, beyond such often short-lived improvements, much…
Comparative graph and network analysis play an important role in both systems biology and pattern recognition, but existing surveys on the topic have historically ignored or underserved one or the other of these fields. We present an…
The present work investigates the relations between amplitude and type of collaboration (intramural, extramural domestic or international) and output of specialized versus diversified research. By specialized or diversified research, we…
PubMed's current search interface makes it tedious to systematically search for medical and research literature on drugs that could potentially be used to treat a given pathology, including patients with genetically altered tumors. This is…
To be successful, junior faculty must properly manage their time in the face of expanding responsibilities. One such responsibility is supervising undergraduate research projects. Student research projects (either single or multi-student)…
Targeting RNA with small molecules offers significant therapeutic potential. Machine learning could substantially accelerate preclinical drug discovery, from hit identification to lead optimization. Yet a fundamental limitation emerges:…
The great behavioral heterogeneity observed between individuals with the same psychiatric disorder and even within one individual over time complicates both clinical practice and biomedical research. However, modern technologies are an…
The fields of therapeutic application and drug research and development (R&D) both face substantial challenges, i.e., the therapeutic domain calls for more treatment alternatives, while numerous promising pre-clinical drugs have failed in…
Quantifying the interdisciplinarity of a research is a relevant problem in the evaluative bibliometrics. The concept of interdisciplinarity is ambiguous and multidimensional. Thus, different measures of interdisciplinarity have been propose…
Understanding the relationship between the composition of a research team and the potential impact of their research papers is crucial as it can steer the development of new science policies for improving the research enterprise. Numerous…
Assessing drug-target affinity is a critical step in the drug discovery and development process, but to obtain such data experimentally is both time consuming and expensive. For this reason, computational methods for predicting binding…
Segregation is a widely recognised phenomenon with profound implications for societies worldwide. From political science and gender studies to anthropology and urban studies, it has garnered considerable attention across numerous scientific…
The majority of big data is unstructured and of this majority the largest chunk is text. While data mining techniques are well developed and standardized for structured, numerical data, the realm of unstructured data is still largely…
Collaborations are an integral part of scientific research and publishing. In the past, access to large-scale corpora has limited the ways in which questions about collaborations could be investigated. However, with improvements in…
Computer science is also an experimental science. This is particularly the case for parallel computing, which is in a total state of flux, and where experiments are necessary to substantiate, complement, and challenge theoretical modeling…