Removed abstracts from paper.bib

paper.bib

@@ -5,28 +5,23 @@ @article{Pulford:2005
          volume = {152},
          number = {5},
          year = {2005},
-         keywords = {target tracking, computational complexity, probability, filtering theory, reviews, estimation theory},
-         abstract = {A concise summary of techniques for multiple target tracking is provided and their main characteristics assessed qualitatively. The techniques have been catergorised into more than 35 different algorithmic types. A comparison chart is provided that lists each algorithm and categorises the processing scheme, data association mechanism, complexity scaling (with number of targets and with state dimension), overall complexity and a subjective performance figure. Although some recent filtering theory developments have been omitted, the survey should serve to demonstrate the large variety of 'classical' estimation theoretic algorithms already available for the design of multiple target tracking systems. A number of areas deserving of further study are identified in the concluding remarks.}
          }
 
 @article{Chenouard:2014,
-        author = {Chenouard N},
-        title = {Objective comparison of particle tracking methods},
-        journal = {Nature Methods},
-        volume = {11},
-        number = {3},
-        year = {2014},
-        abstract = {Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.}
-        }
+         author = {Chenouard N},
+         title = {Objective comparison of particle tracking methods},
+         journal = {Nature Methods},
+         volume = {11},
+         number = {3},
+         year = {2014},
+         }
 
 @article{Tineves:2017,
          author = {Tineves J, Perry N, Schindelin J, Hoopes G M, Reynolds G D, Laplantine E, Bednarek S Y, Shorte S L, and Eliceiri K W},
          title = {TrackMate: An open and extensible platform for single-particle tracking},
          journal = {Methods},
          volume = {115},
          year = {2017},
-         keywords = {Clathin-mediated endocytosis, image analysis, microscopy, open-source software, phototoxicity, single-particle tracking},
-         abstract = {We present TrackMate, an open source Fiji plugin for the automated, semi-automated, and manual tracking of single-particles. It offers a versatile and modular solution that works out of the box for end users, through a simple and intuitive user interface. It is also easily scriptable and adaptable, operating equally well on 1D over time, 2D over time, 3D over time, or other single and multi-channel image variants. TrackMate provides several visualization and analysis tools that aid in assessing the relevance of results. The utility of TrackMate is further enhanced through its ability to be readily customized to meet specific tracking problems. TrackMate is an extensible platform where developers can easily write their own detection, particle linking, visualization or analysis algorithms within the TrackMate environment. This evolving framework provides researchers with the opportunity to quickly develop and optimize new algorithms based on existing TrackMate modules without the need of having to write de novo user interfaces, including visualization, analysis and exporting tools. The current capabilities of TrackMate are presented in the context of three different biological problems. First, we perform Caenorhabditis-elegans lineage analysis to assess how light-induced damage during imaging impairs its early development. Our TrackMate-based lineage analysis indicates the lack of a cell-specific light-sensitive mechanism. Second, we investigate the recruitment of NEMO (NF-κB essential modulator) clusters in fibroblasts after stimulation by the cytokine IL-1 and show that photodamage can generate artifacts in the shape of TrackMate characterized movements that confuse motility analysis. Finally, we validate the use of TrackMate for quantitative lifetime analysis of clathrin-mediated endocytosis in plant cells.}
          }
 
 @article{Wang:2015,
@@ -36,8 +31,6 @@ @article{Wang:2015
          volume = {220},
          number = {PtA},
          year = {2015},
-         keywords = {Diffusion, mucus, multiple particle tracking, single particle tracking, transport},
-         abtract = {Tracking the dynamic motion of individual nanoparticles or viruses offers quantitative insights into their real-time behavior and fate in different biological environments. Indeed, particle tracking is a powerful tool that has facilitated the development of drug carriers with enhanced penetration of mucus, brain tissues and other extracellular matrices. Nevertheless, heterogeneity is a hallmark of nanoparticle diffusion in such complex environments: identical particles can exhibit strongly hindered or unobstructed diffusion within microns of each other. The common practice in 2D particle tracking, namely analyzing all trackable particle traces with equal weighting, naturally biases towards rapidly diffusing sub-populations at shorter time scales. This in turn results in misrepresentation of particle behavior and a systematic underestimate of the time necessary for a population of nanoparticles to diffuse specific distances. We show here via both computational simulation and experimental data that this bias can be rigorously corrected by weighing the contribution by each particle trace on a 'frame-by-frame' basis. We believe this methodology presents an important step towards objective and accurate assessment of the heterogeneous transport behavior of submicron drug carriers and pathogens in biological environments.}
          }
 
 @article{zenodo,