The early introduction of dynamic programming into computational biology
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Notice bibliographique
Résumé
In 1994–1995, DIMACS sponsored a theme year on computational biology. Among the numerous seminars and workshops was one organized by Alberto Apostolico and Raffaele Giancarlo, recapitulated in their 1998 paper, on the history and motivations for sequence comparison. In my participation in this event, I was led to consider some of the early interactions, at the Centre de recherches mathematiques (CRM) and elsewhere, in the field now known as computational biology. A short time earlier, I had read a 1989 paper by Walter Goad on the impact of Stanislaw Ulam in this field. The penultimate sentence in this article was a quote from Ulam himself ‘I started all this’, which puzzled me greatly. As far as I knew, Ulam had no impact in the early development of the field, and while he gave talks on it at least from 1971 (cf. Ulam, 1972), the distance he defined was already published (Levenshtein, 1965) and the problem he proposed had already been solved, for all intents and purposes, in the molecular biology literature (Needleman and Wunsch, 1970) and elsewhere (Vintsyuk, 1968). I had also read a joint interview of Ulam and Mark Kac by Feigenbaum (1982), and this led me to reflect on this misperception on the part of Ulam (and of Goad), and to crystallize the realization that ironically, Kac, his colleague of many years, had played a crucial, if indirect, role in the earliest development of the field, especially that associated with the Centre de recherches mathematiques (CRM). Despite the fact that Kac had no personal research interest in the field, his encouragement of a number of junior mathematicians, and his role, intentional or not, in bringing researchers together, recur as important influences in several aspects of computational biology, and explain why I dedicate this article to his memory. In presenting some of these thoughts to the DIMACS workshop, focusing on the early 1970s, my understanding of this period was broadened by comments from a number of participants, particularly Jerrold Griggs and Pavel Pevzner, and clarified by the presentation immediately
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle