Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.

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Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.

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2017 nî lūn-bûn

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2017年の論文

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年學術文章

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2017年學術文章

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Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.

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Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.

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Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.

@en

Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.

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Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.

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Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.

@nl

P1476

Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.

@en

P2860

Why most published research findings are false

Conceptual biology, hypothesis discovery, and text mining: Swanson's legacy

Extending the mutual information measure to rank inferred literature relationships

A population-based statistical approach identifies parameters characteristic of human microRNA-mRNA interactions

Automating data extraction in systematic reviews: a systematic review

Iron behaving badly: inappropriate iron chelation as a major contributor to the aetiology of vascular and other progressive inflammatory and degenerative diseases

Literature mining for the discovery of hidden connections between drugs, genes and diseases

Entitymetrics: measuring the impact of entities

Reasoning with Vectors: A Continuous Model for Fast Robust Inference

Identifying plausible adverse drug reactions using knowledge extracted from the literature

P304

43-64

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scholarly article

P356

10.1515/JDIS-2017-0019

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P433

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P478

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Neil R. Smalheiser

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2017-12-01T00:00:00Z

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29355246

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5771422

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