27 papers · ranked by Valyu relevance
Matej Usaj, Yizhao Tan, Wen Wang, Benjamin VanderSluis + 5 more
'Chad L. Myers' 'Michael Costanzo' 'Brenda Andrews' 'Charles Boone'] Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by…
Seth I Berger, Jeremy M Posner, Avi Ma'ayan
Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language…
Ehsan Tamandeh, Jessica Bigge, Adrian Serohijos, Johannes Schumacher + 2 more
Human polygenic phenotypes arise from complex interactions among genes within regulatory networks. To gain insights into the structural and evolutionary characteristics of these networks, we analyzed gene interaction networks across 4756 human polygenic phenotypes, contrasting the network properties of genes associated…
Ziqiao Yin, Binghui Guo, Zhilong Mi, Jiahui Li + 1 more
The gene interaction network is one of the most important biological networks and has been studied by many researchers. The gene interaction network provides information about whether the genes in the network can cause or heal diseases. As gene-gene interaction relations are constantly explored, gene interaction…
Raamesh Deshpande, Justin Nelson, Scott W. Simpkins, Michael Costanzo + 4 more
Large-scale genetic interaction screening is a powerful approach for unbiased characterization of gene function and understanding systems-level cellular organization. While genome-wide screens are desirable as they provide the most comprehensive interaction profiles, they are resource and time-intensive and sometimes…
K C Kishan, Rui Li, Feng Cui, Qi Yu + 1 more
The topological landscape of gene interaction networks provides a rich source of information for inferring functional patterns of genes or proteins. However, it is still a challenging task to aggregate heterogeneous biological information such as gene expression and gene interactions to achieve more accurate inference…
Minzhe Zhang, Qiwei Li, Donghyeon Yu, Bo Yao + 3 more
Background Reverse engineering approaches to infer gene regulatory networks using computational methods are of great importance to annotate gene functionality and identify hub genes. Although various statistical algorithms have been proposed, development of computational tools to integrate results from different…
Juan F. Poyatos, Simon Rogers
Genetic interactions are being quantitatively characterized in a comprehensive way in several model organisms. These data are then globally represented in terms of genetic networks. How are interaction strengths distributed in these networks? And what type of functional organization of the underlying genomic systems is…
R James Taylor, Andrew F Siegel, Timothy Galitski
Statistical and computational methods for the extraction of biological information from dense multi-mode genetic-interaction networks were developed and implemented in open-source software.
Viola Fanfani, Giovanni Stracquadanio
Gene and protein interaction experiments provide unique opportunities to study their wiring in a cell. Integrating this information with high-throughput functional genomics data can help identifying networks associated with complex diseases and phenotypes. Here we propose a unified statistical framework to test network…
Ira Horecka, Matej Ušaj, Myra P.D. Masinas, Henry N. Ward + 8 more
Genetic interaction networks map functional connections between genes and their corresponding pathways and complexes. We previously developed TheCellMap.org as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) analysis in the…
Alex J. Cornish, Florian Markowetz
Linking networks of molecular interactions to cellular functions and phenotypes is a key goal in systems biology. Here, we adapt concepts of spatial statistics to assess the functional content of molecular networks. Based on the guilt-by-association principle, our approach (called SANTA) quantifies the strength of…
Magali Michaut, Gary D. Bader, Christian von Mering
Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in…
Carles Pons
Genetic interactions are essential to decipher the complex relationship between genotype and phenotype, which is key to addressing fundamental biology questions and developing therapies for human diseases. However, the scarcity of genetic interaction data in most species hinders research progress. Understanding the…
Chabane Tibiche, Edwin Wang
Lots of gene regulatory relationships have been reported derived 'small-scale' studies. These relations are buried in literature which is rapidly growing. It is extremely timeconsuming and cost-intensive to manually curate gene regulatory relationships by humanreading articles. Therefore, a tool for prioritizing these…
Mehedi Hassan Onik, Shakhawat Ahmmed Nobin, Adnan Ferdous Ashrafi, Tareque Mohmud Chowdhury
'Tareque Mohmud Chowdhury'] Abstract— Reconstruction of gene regulatory networks is the process of identifying gene dependency from gene expression profile through some computation techniques. In our human body, though all cells pose similar genetic material but the activation state may vary. This variation in the…
Avi Ma’ayan, Neil R. Clark
—Popular online enrichment analysis tools from the field of molecular systems biology provide users with the ability to submit their experimental results as gene sets for individual analysis. Such queries are kept private, and have never before been considered as a resource for integrative analysis. By harnessing gene…
Ryan Miller, Sebastian Muraru, Ana Belén Malpartida, Josh Low + 7 more
Within the next twenty years, the number of cancer patients is expected to rise by 70%. Current cancer treatments still face several limitations, such as severe side effects and a high incidence of disease recurrence. Drug combination therapies are a promising strategy to achieve higher therapeutic effects while…
Adrián I. Campos, Julio A. Freyre-González
Genetic regulatory networks (GRNs) have been widely studied, yet there is a lack of understanding with regards to the final size and properties of these networks, mainly due to no network currently being complete. In this study, we analyzed the distribution of GRN structural properties across a large set of distinct…
Giulia Muzio, Leslie O’Bray, Laetitia Meng-Papaxanthos, Juliane Klatt + 1 more
While the search for associations between genetic markers and complex traits has led to the discovery of tens of thousands of trait-related genetic variants, the vast majority of these only explain a small fraction of observed phenotypic variation. One possible strategy to detect stronger associations is to aggregate…
Dariia Yehorova, Rory Crean, Peter Kasson, Shina Caroline Lynn Kamerlin
Protein structure (and thus function) is dictated by non-covalent interaction networks. These can be highly evolutionarily conserved across protein families, the members of which can diverge in sequence and evolutionary history. Here we present KIN, a tool to identify and analyze conserved non-covalent interaction…
Salvatore Miccichè
The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The Gene Ontology is constantly evolving over time. The information accumulated time-by-time and included in the GO is encoded in the…
Abhijeet R. Sonawane, Scott T. Weiss, Kimberly Glass, Amitabh Sharma
Network medicine is an emerging area of research dealing with molecular and genetic interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale biomedical data generation offers a unique opportunity to assess the effect and impact of cellular heterogeneity and environmental perturbations…
Javier Santos-Moreno, Eve Tasiudi, Hadiastri Kusumawardhani, Joerg Stelling + 1 more
Genotype networks are sets of genotypes connected by small mutational changes that share the same phenotype. They facilitate evolutionary innovation by enabling the exploration of different neighborhoods in genotype space. Genotype networks, first suggested by theoretical models, have been empirically confirmed for…
Giovanni Marco Dall’Olio, Ali R. Vahdati, Bertranpetit Jaume, Andreas Wagner + 1 more
'Andreas Wagner' 'Laayouni Hafid'] Summary: Genotype networks are a method used in systems biology to study the innovability of a given phenotype, determining whether the phenotype is robust to mutations, and how do the genotypes associated to it are distributed in the genotype space. Here we developed VCF2Networks, a…
Nedra Mekni, Hosein Fooladi, Ugo Perricone, Thierry Langer
Machine learning models are employed to enhance the speed and provide novel insights in drug discovery due to their demonstrated effectiveness in predicting properties of small molecules like pKa, solubility, and binding affinity. These approaches accelerate drug discovery by helping researchers efficiently identify…
Zhiwen Pan, Jan Dellith, Lothar Wondraczek
Understanding the multivariate origin of physical properties is particularly complex for polyionic glasses. As a concept, the term genome has been used to describe the entirety of structure-property relations in solid materials, based on functional genes acting as descriptors for a particular property, for example, for…