MicroRNAs (miRs) are robust regulators of gene expression, implicated in most biological processes. microRNAs predominantly downregulate the expression of genes post-transcriptionally and each miR is predicted to target several hundred genes. The accurate identification and annotation of miR-mRNA target interactions is central to understanding miRs function and their therapeutic potential. However, computational target prediction is challenging due to imperfect complementarity of miRs with their targets and the growing volume and heterogeneity of experimental data present challenges in accessing, integrating, and analysing miR-target interaction information across biological contexts. This creates a need for integrated resources and intelligent query tools. We present the miRKat Suite, comprising miRKatDB, a comprehensive, curated database of predicted and validated miR-target interactions and associated annotations, and miRKatAI, a multi-agent system powered by large language models (LLMs) and LangGraph. miRKatDB integrates data from multiple publicly available sources, providing a comprehensive foundation for miR studies, including miR target genes and changes in levels of tissue expression previously reported. miRKatAI offers a natural language interface for complex querying of miRKatDB, facilitates grounded information retrieval from established sources in the field, and supports basic data visualisation. The miRKat Suite aims to accelerate miR research by streamlining data access, enhancing exploratory analysis, and supporting hypothesis generation.

SSENSE (pronounced [es-uhns]) is a global technology platform operating at the intersection of culture, community, and commerce. Headquartered in Montreal, it features a mix of established and emerging luxury brands across womenswear, menswear, kidswear, and Everything Else. SSENSE has garnered critical acclaim as both an e-commerce engine and a producer of cultural content, generating an average of 100 million monthly page views. Approximately 80% of its audience is between the ages of 18 to 40. It is privately held and has achieved high double digit annual growth and profitability since its inception.

Environment Canterbury (ECan) has taken its first steps towards using artificial intelligence to identify pest plants from aerial imagery. A successful pilot programme in South Canterbury has shown that AI may provide a more efficient way to inspect large swathes of land for biosecurity threats such as Nassella tussock. The tussock is an invasive grass that is rapidly spreading in Canterbury. It displaces productive pastures and is unpalatable to stock. Only 70 years ago, Nassella drove some farmers off the land after it ran rampant, taking over entire farms, leaving no room for crops or stock.

SSENSE (pronounced [es-uhns]) is a global technology platform operating at the intersection of culture, community, and commerce. Headquartered in Montreal, it features a mix of established and emerging luxury brands across womenswear, menswear, kidswear, and Everything Else. SSENSE has garnered critical acclaim as both an e-commerce engine and a producer of cultural content, generating an average of 100 million monthly page views. Approximately 80% of its audience is between the ages of 18 to 40. It is privately held and has achieved high double digit annual growth and profitability since its inception.

In the previous post, I explored how useful ChatGPT currently is for data visualisation. This was done through testing this AI tool on a number of tasks and on its information retrieval ability. The results showed that ChatGPT still had some way to go on the theory and consulting side of things, as it still made mistakes and had limited knowledge on the subject. Despite this, it's still impressive how it can easily provide a written response that was mostly correct for what I had asked. Where ChatGPT really shined was on the coding side of DataViz.

Data scientists are critical to the success of many fintech firms, but the area is still relatively young and unproven. As technology advances, data scientists must stay up with new breakthroughs and adapt their skill sets accordingly. Real-time analytics, consumer analytics, algorithmic trading, Robo-advisors, financial planning, and other applications of data science in the FinTech industry are useful. Some tech-savvy entrepreneurs are attempting to establish wholly new information services firms of data captured, managed, and analyzed utilizing FinTech data science. Several variables are driving the "Big Data" (or "information services") opportunity in FinTech, but I'll focus on just two.

Getting into the dynamic field of data science requires you to catch up and build on the trends of the industry. Building your portfolio is the right direction for it and solving the existing problems that can orchestrate breakthroughs in the industry is the perfect path to take. Finding the right project that fits your knowledge, matches with requirements of the industry, and gives you real world practical experience is a decision-heavy task. We have compiled a list of trending data science projects that you can explore to help refine your resume and land a job of your choice in 2023! For natural language processing, this data science project involves determining whether the data inferred is positive, negative, or neutral.

All the Data Scientists hide at least on Data Science idea in their heart. However, due to time constraints or lack of money, they do not transform their ideas into a project. In this article, I propose a strategy to turn your idea into a Data Science project. The first step towards funding your project involves writing a first draft your project. The summary is an overview of the project.

The thriving industry of Data Science is continuously evolving with the technological advancements in Machine Learning and Artificial intelligence. This has opened up whole new avenues for Data Scientists worldwide. Professionals who can handle Big Data and have the necessary knowledge required for understanding, analysing and processing data are in high demand in the job market. However, there is one important thing that also needs to be addressed is the raging problem caused by the gender gap in this sector. As per the statistical report from the Boston Consulting Group, only 15 to 22 per cent of the Data Science-related professional roles are occupied by women.

With the rise of podcasts and YouTubers taking over the social media world, informing people on what's happened, what's new, and more. The best knowledge is still placed in the libraries; within books. Learning on the web has become a new way of learning. However, most of these studies were all once upon a time written down. A lot of people are interested in getting into the world of Data Science, however, it can be difficult to choose which path to go down and the correct resources.