Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future

Abstract

“Α picture is worth a thousand words.” This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information. Although, in general, the notion of capturing complex ideas using images is very appealing, would 1000 words be enough to describe the unknown in a research field such as the life sciences? Life sciences is one of the biggest generators of enormous datasets, mainly as a result of recent and rapid technological advances; their complexity can make these datasets incomprehensible without effective visualization methods. Here we discuss the past, present and future of genomic and systems biology visualization. We briefly comment on many visualization and analysis tools and the purposes that they serve. We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further.

A Network Biology Approach to Decipher Stress Response in Bacteria UsingEscherichia coliAs a Model

“…2 Laboratory of Molecular Biology and Genetic Engineering, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India. diseases can be captured (Gupta et al, 2015;Vinayagam et al, 2015). Network studies have previously been used to encapsulate big data into a single picture, allowing inference of novel concepts and conclusion (Pavlopoulos et al, 2015;Vinayagam et al, 2015). Network studies in bacteria have been used to elucidate functional aspects (Kumar et al, 2016;Purves et al, 2016;Typas and Sourjik, 2015).…”

Computational Errors and Biases in Short Read Next Generation Sequencing

“…Nice visualization is provided by IGV [128] and GAP5 [129,130]. There are good visualization genome reviews [131,132].…”

Valorizing omics visualization for discovery

“…Clearly, visualizations are necessary for the adoption, use, and efficacy of uptake of computational methods in data science. Major efforts have been made in recent years to create visualization tools that can extract useful knowledge from the vast amount of data generated by high-throughput technologies [10,29,37]. However, more progress is required to create new tools to meet the changing needs of the field.…”

“…The omics technologies (genomics, transcriptomics, proteomics, metabolomics, lipidomics, etc.) have generated many multifactorial experiments that necessitate effective visual exploration by life science experts to successfully extract knowledge [10,29,37]. The challenge in practical terms is how to present the data at the right level of detail, in a cohesive, insightful manner.…”