Measuring the State of the Art of Automated Pathway Curation Using
            Graph Algorithms - A Case Study of the mTOR Pathway

Spranger, Michael; Palaniappan, Sucheendra K.; Ghosh, Samik

doi:10.18653/v1/w16-2916

Cited by 4 publications

(9 citation statements)

References 29 publications

(34 reference statements)

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“…Of particular note is the DREAM network inference challenge where prior-based methods took the top two positions in an independent evaluation ( 18 ). Others have looked at the overlap between curated models and literature-derived networks ( 25 , 37 ). Our work is the first to carefully examine whether the biochemical pathways extracted by the machine can be successfully combined with human-curated models in the context of a specific analytical task.…”

Section: Extrinsic Evaluation: Discovery Of Biological Hypothesesmentioning

confidence: 99%

Large-scale automated machine reading discovers new cancer-driving mechanisms

et al. 2018

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PubMed, a repository and search engine for biomedical literature, now indexes >1 million articles each year. This exceeds the processing capacity of human domain experts, limiting our ability to truly understand many diseases. We present Reach, a system for automated, large-scale machine reading of biomedical papers that can extract mechanistic descriptions of biological processes with relatively high precision at high throughput. We demonstrate that combining the extracted pathway fragments with existing biological data analysis algorithms that rely on curated models helps identify and explain a large number of previously unidentified mutually exclusive altered signaling pathways in seven different cancer types. This work shows that combining human-curated ‘big mechanisms’ with extracted ‘big data’ can lead to a causal, predictive understanding of cellular processes and unlock important downstream applications.

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Section: Extrinsic Evaluation: Discovery Of Biological Hypothesesmentioning

confidence: 99%

Large-scale automated machine reading discovers new cancer-driving mechanisms

et al. 2018

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“…Spranger et al (2016) propose a number of graph overlap algorithms for quantifying the difference and similarity of two pathways. Here we employ the same measures.…”

Section: Discussionmentioning

confidence: 99%

“…If we analyze the classifiers from this paper in more detail, results (Figure 1, Table 4: This table compares macro F-score performance of the classifiers discussed in this paper with results reported in Spranger et al (2016) for the strictest matching strategy (nmeq, sboeq) the best classifiers reach a macro F-score of 12…”

Section: General Trends Subgraphs Overlapmentioning

confidence: 94%

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BioNLP 2017

Cohen¹,

Demner‐Fushman²,

Ananiadou³

et al. 2017

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According to the Association for Computational Linguistics guidelines on special interest groups (SIGs), The function of a SIG is to encourage interest and activity in specific areas within the ACL's field [1]. Is the SIGBioMed special interest group "within the ACL's field"? The titles of this year's papers suggest that it is, in that the current interest in deep learning in its many and varied manifestations is mirrored in those titles. Do those papers cover a specific area? They do, and in doing so, they demonstrate one of the great satisfactions of working in biomedical natural language processing.One of the joys of involvement in the biomedical natural language processing community is seeing the development of research with clinical applications. As examples of such work being presented at BioNLP 2017, we would like to point out the two papers that discuss the application of natural language processing to the diagnosis of neurological disorders. Bhatia et al. [2] describe an approach to using speech processing in the assessment of patients with amyotrophic lateral sclerosis (also known as Lou Gehrig's disease), one of the more horrific motor neuron diseases. Good assessment of amyotrophic lateral sclerosis patients is important for a number of reasons, including the fact that accurate tracking of the inevitable deterioration that is a hallmark of this disease gives patients and their families the possibility of purposeful planning for the attendant disability and death. However, current methodologies for evaluating the status of amyotrophic lateral sclerosis patients necessarily involve expensive equipment and highly trained personnel; when further developed, this methodology could make such evaluation much more, and more frequently, available to ALS patients. The fact that the work reported here involves a speech modality is especially exciting, as speech-related indicators of future ALS can be present long before diagnosis. The paper uses measurements of phonological features of speech and their divergence from a baseline, and demonstrates correlation with physiological measures.Adams et al. [3] describe work on detecting and categorizing word production errors associated with anomia, a particular kind of inability to find words. Screening for anomia is important because anomia is a symptom of stroke, but it is difficult and time-consuming to do, and therefore is not done as often as it should be. Automatic detection of anomia could be a nice enabler of improved care for stroke victims, but it is made difficult due to the subtlety of the phonological and semantic judgments that have to be made when assessing the phenomenon. The paper uses a combination of language modeling and phonologically-based edit distance calculation to approach the task, applying these techniques to data from the AphasiaBank collection of transcribed aphasic and healthy speech.Although we have summarized only these two examples that address neurological disorders, there are several other papers on the use of natural language proc...

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“…Recently, there has been some attempt at remedying the situation and new datasets and evaluation measures have been proposed. For instance, Spranger et al (2016) use the popular human-generated mTOR pathway map (Caron et al, 2010;Efeyan and Sabatini, 2010;Katiyar et al, 2009) and quantify the performance of a particular APC system and its ability to recreate the complete pathway automatically. Results reported were mixed.…”

Section: Introductionmentioning

confidence: 99%