Domain-topic models with chained dimensions: Charting an emergent domain of a major oncology conference.

This paper presents a contribution to the study of bibliographic corpora through science mapping. From a graph representation of documents and their textual dimension, stochastic block models can provide a simultaneous clustering of documents and words that we call a domain-topic model. Previous work investigated the resulting topics, or word clusters, while ours focuses on the study of the document clusters we call domains.

Mapping the Emergence of Synthetic Biology.

In this paper, we apply an original scientometric analyses to a corpus comprising synthetic biology (SynBio) publications in Thomson Reuters Web of Science to characterize the emergence of this new scientific field. Three results were drawn from this empirical investigation. First, despite the exponential growth of publications, the study of population level statistics (newcomers proportion, collaboration network structure) shows that SynBio has entered a stabilization process since 2010.

Lexical shifts, substantive changes, and continuity in State of the Union discourse, 1790-2014.

This study reveals that the entry into World War I in 1917 indexed the decisive transition to the modern period in American political consciousness, ushering in new objects of political discourse, a more rapid pace of change of those objects, and a fundamental reframing of the main tasks of governance. We develop a strategy for identifying meaningful categories in textual corpora that span long historic durées, where terms, concepts, and language use changes. Our approach is able to account for the fluidity of discursive categories over time, and to analyze their continuity by identifying the discursive stream as the object of interest.

LinkRbrain: multi-scale data integrator of the brain.

Background: LinkRbrain is an open-access web platform for multi-scale data integration and visualization of human brain data. This platform integrates anatomical, functional, and genetic knowledge produced by the scientific community.

New Method: The linkRbrain platform has two major components: (1) a data aggregation component that integrates multiple open databases into a single platform with a unified representation; and (2) a website that provides fast multi-scale integration and visualization of these data and makes the results immediately available.

Therapy's Shadow: A Short History of the Study of Resistance to Cancer Chemotherapy.

This article traces the history of research on resistance to drug therapy in oncology using scientometric techniques and qualitative analysis. Using co-citation analysis, we generate maps to visualize subdomains in resistance research in two time periods, 1975-1990 and 1995-2010. These maps reveal two historical trends in resistance research: first, a shift in focus from generic mechanisms of resistance to chemotherapy to a focus on resistance to targeted therapies and molecular mechanisms of oncogenesis; and second, a movement away from an almost exclusive reliance on animal and cell models and toward the generation of knowledge about resistance through clinical trial work.

Phylomemetic patterns in science evolution--the rise and fall of scientific fields.

We introduce an automated method for the bottom-up reconstruction of the cognitive evolution of science, based on big-data issued from digital libraries, and modeled as lineage relationships between scientific fields. We refer to these dynamic structures as phylomemetic networks or phylomemies, by analogy with biological evolution; and we show that they exhibit strong regularities, with clearly identifiable phylomemetic patterns. Some structural properties of the scientific fields - in particular their density -, which are defined independently of the phylomemy reconstruction, are clearly correlated with their status and their fate in the phylomemy (like their age or their short term survival).

[The emergence and development of gene expression profiling: a key component of the 3B (bench, bedside, bytes) in translational research].

This paper examines the emergence and development of one of the key components of genomics, namely gene expression profiling. It does so by resorting to computer-based methods to analyze and visualize networks of scientific publications. Our results show the central role played by oncology in this domain, insofar as the initial proof-of-principle articles based on a plant model organism have quickly led to the demonstration of the value of these techniques in blood cancers and to applications in the field of solid tumors, and in particular breast cancer.