Studying the association of gene function, diseases, and regulatory gene network reconstruction demands data compatibility. Data from different databases follow distinct schemas and are accessible in heterogenic ways. Although the experiments differ,...
The advancement of computational genomics has significantly enhanced the use of data-driven solutions in disease prediction and precision medicine. Yet, challenges such as data scarcity, privacy constraints, and biases persist. Synthetic data generat...
Biomedical data (structured and unstructured) has grown dramatically in strength and volume over the last few years. Innovative, intelligent, and autonomous scientific approaches are needed to examine the large data sets that are gradually becoming w...
Biological nitrogen removal (BNR) technologies are the most effective approaches for the remediation of environmental nitrogen pollutants from wastewater treatment plants (WWTPs). Presently, research is going on to elucidate the structure and functio...
Background: The modeling of Biological Regulatory Networks (BRNs) relies on background knowledge, deriving either from literature and/or the analysis of biological observations. However, with the development of high-throughput data, there is a growin...
In the past few decades, we have witnessed tremendous advancements in biology, life sciences and healthcare. These advancements are due in no small part to the big data made available by various high-throughput technologies, the ever-advancing comput...
Biological nanonetworks have been envisaged to be the most appropriate alternatives to classical electromagnetic nanonetworks for applications in biological environments. Due to the diffusional method of the message exchange process, transfer data ra...
To elucidate ecosystem functioning, it is fundamental to recognize what processes occur in which environments (where) and which microorganisms carry them out (who). Here, we present PREGO, a one-stop-shop knowledge base providing such associations. P...
In large datasets, irrelevant, redundant, and noisy attributes are often present. These attributes can have a negative impact on the classification model accuracy. Therefore, feature selection is an effective pre-processing step intended to enhance t...
Massive heterogeneous big data residing at different sites with various types and formats need to be integrated into a single unified view before starting data mining processes. Furthermore, in most of applications and research, a single big data sou...
The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clin...
The ever increasing growth of the production of high-throughput sequencing data poses a serious challenge to the storage, processing and transmission of these data. As frequently stated, it is a data deluge. Compression is essential to address this c...
Psoriasis is a chronic, inflammatory skin disease occurring worldwide that significantly affects patients’ quality of life. This common skin condition is characterized by abnormal hyperplasia of keratinocytes, which leads to the formation of ra...
Advances in knowledge about clinical features, physiology, and underlying immunology are leading to targeted therapies and a new era of therapies. Biological treatments for severe asthma have changed the way this disease is managed, especially in pat...
With the increasing speed of genomic, transcriptomic, and metagenomic data generation driven by the advancement and widespread adoption of next-generation sequencing technologies, the management and analysis of large-scale, diverse data in the fields...
Increasingly amounts of biological data promote the development of various penalized regression models. This review discusses the recent advances in both linear and logistic regression models with penalization terms. This review is mainly focused on...
Big data approaches are rapidly expanding across many fields of science and are seeing increasing application, yet the use of big data in research related to invasive species lags. Big data can play a key role in predicting, detecting, preventing, co...
Background: Biological aging influences cancer outcomes, but its changes during chemotherapy and impact on chemotoxicity in colorectal cancer (CRC) remain underinvestigated. We examined (1) trajectories of biological aging (using Levine Phenotypic Ag...
Data analysis used for biomedical research, particularly analysis involving metabolic or signaling pathways, is often based upon univariate statistical analysis. One common approach is to compute means and standard deviations individually for each va...
Cynometra L. is a Fabaceae genus that is widely distributed throughout the tropics, consisting of tropical forest trees with ecological and economic importance since they are used as food and herbal medicines by the populations of their natural habit...
The article presents and discusses the issues of the use of free-living invertebrates to assess the ecological status of freshwater environments with different methods of biological monitoring. Invertebrates are excluded from ethical consideration in...
The impact of invasive alien species (IAS) on nature and society is increasing globally. It is crucial to utilize information systems for evidence-based management, enabling the assessment and supporting survey and control actions. However, the lack...
In the last two decades, there have been massive advancements in high throughput technologies, which resulted in the exponential growth of public repositories of gene expression datasets for various phenotypes. It is possible to unravel biomarkers by...
This study introduces a novel framework that simultaneously addresses the challenges of performance accuracy and result interpretability in transcriptomic-data-based classification. Background/objectives: In biological data classification, it is chal...
Policy learning enables agents to learn how to map states to actions, thus enabling adaptive and flexible behavioral generation in complex environments. Policy learning methods are fundamental to reinforcement learning techniques. However, as problem...
Synthetic biology, an emergent interdisciplinary field integrating principles from biology, engineering, and computer science, endeavors to rationally design and construct novel biological systems or reprogram extant ones to achieve predefined functi...
1 November 2018
Purpose Biological age (BA) has recently emerged as a substitute for chronological age (CA), and many subjects seek to optimally control their BA. However, in South Korea, no study has adequately explored factors that affect BA, although individual h...
Metabolites are at the end of the gene–transcript–protein–metabolism cascade. As such, metabolomics is the omics approach that offers the most direct correlation with phenotype. This allows, where genomics, transcriptomics and prote...
The effects of low doses of toxicants are often subtle and information extracted from metabolomic data alone may not always be sufficient. As end products of enzymatic reactions, metabolites represent the final phenotypic expression of an organism an...
Biological technology allows us to invent new medical approaches, create effective food production methods and reserves and develop new materials for industrial production. There is a diversity of biological technology types, and different technologi...
26 August 2021
In the case of rapid outbreaks of infectious diseases in remote locations, the lack of real-time information from the field and rapid spread of misinformation can be a major issue. To improve situational awareness and decision-making at all levels of...
Univariate analyses of metabolomics data currently follow a frequentist approach, using p-values to reject a null hypothesis. We here propose the use of Bayesian statistics to quantify evidence supporting different hypotheses and discriminate between...
Single-cell measurements incorporate invaluable information regarding the state of each cell and its underlying regulatory mechanisms. The popularity and use of single-cell measurements are constantly growing. Despite the typically large number of co...
Generating realistic synthetic gene expression data that captures the complex interdependencies and biological context of cellular systems remains a significant challenge. Existing methods often struggle to reproduce intricate co-expression patterns...
Proteomics and genomics discovery experiments generate increasingly large result tables, necessitating more researcher time to convert the biological data into new knowledge. Literature review is an important step in this process and can be tedious f...
MycelialNet is a novel deep neural network (DNN) architecture inspired by natural mycelial networks. Mycelia, the vegetative part of fungi, form extensive underground networks that, in a very efficient way, connect biological entities, transport nutr...
The genus Callyspongia (Callyspongiidae) encompasses a group of demosponges including 261 described species, of which approximately 180 have been accepted after taxonomic reviews. The marine organisms of Callyspongia are distributed in tropical ecosy...
Following the explosive growth in chemical and biological data, the shift from traditional methods of drug discovery to computer-aided means has made data mining and machine learning methods integral parts of today’s drug discovery process. In this p...
The integrated assessment of ecological quality in estuarine ecosystems holds significant importance for environmental management. Previous monitoring programs predominantly focused on environmental data, lacking a comprehensive quality assessment ap...
The importance of clinical information related to specimens is increasing due to the research on human biological specifications being conducted worldwide. In order to utilize data, it is necessary to define the range of data and develop a standardiz...
Background: Immune checkpoint inhibitors (ICIs) are now a therapeutic standard in advanced non-small cell lung cancer (NSCLC), but strong predictive markers for ICIs efficacy are still lacking. We evaluated machine learning models built on simple cli...
Advances in metagenomics have revolutionized our ability to elucidate links between the microbiome and human diseases. Colorectal cancer (CRC), a leading cause of cancer-related mortality worldwide, has been associated with dysbiosis of the gut micro...
Gold nanorods (GNRs) showed to be a suitable contrast agent in photoacoustics (PA), and are able to provide a tunable absorption contrast against background tissue, while a detectable PA signal can be generated from highly localized and targeted area...
Cajanus cajan (aka pigeon pea) is a terrestrial medicinal plant native to Asian and African countries before being introduced to the American continent. This protein-rich legume species, belonging to the Fabaceae family, has been traditionally used t...
Biological growth represents one of the main threats for the conservation of subterranean cultural heritage. Knowledge of the conditions which favour the various taxonomic groups is important in delineating their control methods. Combining our experi...
Clinical routine in proton therapy currently neglects the radiobiological impact of nuclear target fragments generated by proton beams. This is partially due to the difficult characterization of the irradiation field. The detection of low energetic f...
Post-marketing surveillance is essential to evaluate the risk/benefit profile of drugs; however, pharmacovigilance studies comparing persistence and safety of biologic therapies in patients with inflammatory bowel disease (IBD) are scant. The aim of...
Predictive models based on empirical similarity are instrumental in biology and data science, where the premise is to measure the likeness of one observation with others in the same dataset. Biological datasets often encompass data that can be catego...
The rapid advancements in high-throughput technologies have led to a dramatic increase in diverse -omics data types, enabling comprehensive analyses, especially for complex diseases like cancer. Despite the development of multi-omics approaches, the...
Background/Objectives: Predicting treatment persistence in inflammatory bowel disease (IBD) remains challenging despite a broadened therapeutic arsenal. This study used longitudinal data to assess drug persistence across four biologics for IBD prior...
of 283